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Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
[[package]]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
name = "accelerate"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
version = "0.29.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Accelerate"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
python-versions = ">=3.8.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
{file = "accelerate-0.29.3-py3-none-any.whl", hash = "sha256:99d633d4b6126817c5e554487406748be95c8d1d1e659dd2fd60657e35f532dd"},
{file = "accelerate-0.29.3.tar.gz", hash = "sha256:1a5a845b06b24b41736b219b2b20fd021ca5dff4070a252445fd6de736e347ac"},
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
]
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
huggingface-hub = "*"
numpy = ">=1.17"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
packaging = ">=20.0"
psutil = "*"
pyyaml = "*"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
safetensors = ">=0.3.1"
torch = ">=1.10.0"
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.2.1,<0.3.0)", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.2.1,<0.3.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
rich = ["rich"]
sagemaker = ["sagemaker"]
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
test-dev = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
testing = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
[[package]]
name = "aiohappyeyeballs"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "2.4.3"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
description = "Happy Eyeballs for asyncio"
optional = true
python-versions = ">=3.8"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
]
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
[[package]]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
name = "aiohttp"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "3.10.10"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Async http client/server framework (asyncio)"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
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Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
aiohappyeyeballs = ">=2.3.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
aiosignal = ">=1.1.2"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
attrs = ">=17.3.0"
frozenlist = ">=1.1.1"
multidict = ">=4.5,<7.0"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
yarl = ">=1.12.0,<2.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "aiosignal"
version = "1.3.1"
description = "aiosignal: a list of registered asynchronous callbacks"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=3.7"
files = [
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
{file = "aiosignal-1.3.1-py3-none-any.whl", hash = "sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17"},
{file = "aiosignal-1.3.1.tar.gz", hash = "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
frozenlist = ">=1.1.0"
v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
[[package]]
name = "annotated-types"
Upgrading all versions. (#1759)
2024-04-18 15:17:40 +00:00
version = "0.7.0"
v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
description = "Reusable constraint types to use with typing.Annotated"
optional = true
python-versions = ">=3.8"
files = [
Upgrading all versions. (#1759)
2024-04-18 15:17:40 +00:00
{file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
{file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "async-timeout"
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
version = "4.0.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Timeout context manager for asyncio programs"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
{file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
{file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "attrs"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "24.2.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Classes Without Boilerplate"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=3.7"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"},
{file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"},
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
[[package]]
name = "bitsandbytes"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "0.43.3"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
description = "k-bit optimizers and matrix multiplication routines."
optional = true
python-versions = "*"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "bitsandbytes-0.43.3-py3-none-manylinux_2_24_x86_64.whl", hash = "sha256:cc99507c352be0715098b2c7577b690dd158972dc4ea10c7495bac104c7c79f0"},
{file = "bitsandbytes-0.43.3-py3-none-win_amd64.whl", hash = "sha256:257f6552f2144748a84e6c44e1f7a98f3da888f675ed74e18fd7f7eb13c6cafa"},
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
]
[package.dependencies]
numpy = "*"
torch = "*"
[package.extras]
benchmark = ["matplotlib", "pandas"]
test = ["scipy"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "certifi"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2024.8.30"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Python package for providing Mozilla's CA Bundle."
optional = false
python-versions = ">=3.6"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "charset-normalizer"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "3.4.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
optional = false
python-versions = ">=3.7.0"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "click"
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 12:28:22 +00:00
version = "8.1.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Composable command line interface toolkit"
optional = false
python-versions = ">=3.7"
files = [
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 12:28:22 +00:00
{file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"},
{file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
colorama = {version = "*", markers = "platform_system == \"Windows\""}
v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
[[package]]
name = "cloudpickle"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "3.1.0"
v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
description = "Pickler class to extend the standard pickle.Pickler functionality"
optional = true
python-versions = ">=3.8"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "cloudpickle-3.1.0-py3-none-any.whl", hash = "sha256:fe11acda67f61aaaec473e3afe030feb131d78a43461b718185363384f1ba12e"},
{file = "cloudpickle-3.1.0.tar.gz", hash = "sha256:81a929b6e3c7335c863c771d673d105f02efdb89dfaba0c90495d1c64796601b"},
v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "colorama"
version = "0.4.6"
description = "Cross-platform colored terminal text."
optional = false
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
{file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "datasets"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "2.14.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "HuggingFace community-driven open-source library of datasets"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=3.8.0"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "datasets-2.14.4-py3-none-any.whl", hash = "sha256:29336bd316a7d827ccd4da2236596279b20ca2ac78f64c04c9483da7cbc2459b"},
{file = "datasets-2.14.4.tar.gz", hash = "sha256:ef29c2b5841de488cd343cfc26ab979bff77efa4d2285af51f1ad7db5c46a83b"},
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
aiohttp = "*"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
dill = ">=0.3.0,<0.3.8"
fsspec = {version = ">=2021.11.1", extras = ["http"]}
huggingface-hub = ">=0.14.0,<1.0.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
multiprocess = "*"
numpy = ">=1.17"
packaging = "*"
pandas = "*"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
pyarrow = ">=8.0.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
pyyaml = ">=5.1"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
requests = ">=2.19.0"
tqdm = ">=4.62.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
xxhash = "*"
[package.extras]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
apache-beam = ["apache-beam (>=2.26.0,<2.44.0)"]
audio = ["librosa", "soundfile (>=0.12.1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
dev = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "black (>=23.1,<24.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "pyyaml (>=5.3.1)", "rarfile (>=4.0)", "ruff (>=0.0.241)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
docs = ["s3fs", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos", "torch", "transformers"]
jax = ["jax (>=0.2.8,!=0.3.2,<=0.3.25)", "jaxlib (>=0.1.65,<=0.3.25)"]
metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk", "requests-file (>=1.5.1)", "rouge-score", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "spacy (>=3.0.0)", "texttable (>=1.6.3)", "tldextract", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "typer (<0.5.0)"]
quality = ["black (>=23.1,<24.0)", "pyyaml (>=5.3.1)", "ruff (>=0.0.241)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
s3 = ["s3fs"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos"]
tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
torch = ["torch"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
vision = ["Pillow (>=6.2.1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 19:54:39 +00:00
name = "deprecated"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
version = "1.2.14"
description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
{file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
{file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
wrapt = ">=1.10,<2"
[package.extras]
dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
[[package]]
name = "dill"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "0.3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "serialize all of Python"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
optional = false
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "dill-0.3.7-py3-none-any.whl", hash = "sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e"},
{file = "dill-0.3.7.tar.gz", hash = "sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03"},
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
graph = ["objgraph (>=1.7.2)"]
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "diskcache"
version = "5.6.3"
description = "Disk Cache -- Disk and file backed persistent cache."
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3"
files = [
{file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"},
{file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"},
]
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
[[package]]
name = "einops"
version = "0.6.1"
description = "A new flavour of deep learning operations"
optional = false
python-versions = ">=3.7"
files = [
{file = "einops-0.6.1-py3-none-any.whl", hash = "sha256:99149e46cc808956b174932fe563d920db4d6e5dadb8c6ecdaa7483b7ef7cfc3"},
{file = "einops-0.6.1.tar.gz", hash = "sha256:f95f8d00f4ded90dbc4b19b6f98b177332614b0357dde66997f3ae5d474dc8c8"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "exceptiongroup"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
version = "1.2.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Backport of PEP 654 (exception groups)"
optional = false
python-versions = ">=3.7"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
{file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
{file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
test = ["pytest (>=6)"]
[[package]]
name = "filelock"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "3.16.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "A platform independent file lock."
optional = false
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 12:28:22 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "filelock-3.16.1-py3-none-any.whl", hash = "sha256:2082e5703d51fbf98ea75855d9d5527e33d8ff23099bec374a134febee6946b0"},
{file = "filelock-3.16.1.tar.gz", hash = "sha256:c249fbfcd5db47e5e2d6d62198e565475ee65e4831e2561c8e313fa7eb961435"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4.1)"]
testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.2)", "pytest (>=8.3.3)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.4)"]
typing = ["typing-extensions (>=4.12.2)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "frozenlist"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
version = "1.4.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "A list-like structure which implements collections.abc.MutableSequence"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=3.8"
files = [
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "fsspec"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "2024.10.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "File-system specification"
optional = false
python-versions = ">=3.8"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
aiohttp = {version = "<4.0.0a0 || >4.0.0a0,<4.0.0a1 || >4.0.0a1", optional = true, markers = "extra == \"http\""}
[package.extras]
abfs = ["adlfs"]
adl = ["adlfs"]
arrow = ["pyarrow (>=1)"]
dask = ["dask", "distributed"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
dev = ["pre-commit", "ruff"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
dropbox = ["dropbox", "dropboxdrivefs", "requests"]
full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
fuse = ["fusepy"]
gcs = ["gcsfs"]
git = ["pygit2"]
github = ["requests"]
gs = ["gcsfs"]
gui = ["panel"]
hdfs = ["pyarrow (>=1)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
libarchive = ["libarchive-c"]
oci = ["ocifs"]
s3 = ["s3fs"]
sftp = ["paramiko"]
smb = ["smbprotocol"]
ssh = ["paramiko"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
tqdm = ["tqdm"]
[[package]]
name = "googleapis-common-protos"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "1.65.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Common protobufs used in Google APIs"
optional = false
python-versions = ">=3.7"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "googleapis_common_protos-1.65.0-py2.py3-none-any.whl", hash = "sha256:2972e6c496f435b92590fd54045060867f3fe9be2c82ab148fc8885035479a63"},
{file = "googleapis_common_protos-1.65.0.tar.gz", hash = "sha256:334a29d07cddc3aa01dee4988f9afd9b2916ee2ff49d6b757155dc0d197852c0"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
[[package]]
name = "grpc-interceptor"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
version = "0.15.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Simplifies gRPC interceptors"
optional = false
python-versions = ">=3.7,<4.0"
files = [
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
grpcio = ">=1.49.1,<2.0.0"
[package.extras]
testing = ["protobuf (>=4.21.9)"]
[[package]]
name = "grpcio"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "1.67.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "HTTP/2-based RPC framework"
optional = false
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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{file = "grpcio-1.67.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:391df8b0faac84d42f5b8dfc65f5152c48ed914e13c522fd05f2aca211f8bfad"},
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{file = "grpcio-1.67.0-cp39-cp39-win32.whl", hash = "sha256:30d47dbacfd20cbd0c8be9bfa52fdb833b395d4ec32fe5cff7220afc05d08571"},
{file = "grpcio-1.67.0-cp39-cp39-win_amd64.whl", hash = "sha256:f55f077685f61f0fbd06ea355142b71e47e4a26d2d678b3ba27248abfe67163a"},
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
protobuf = ["grpcio-tools (>=1.67.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "grpcio-reflection"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Standard Protobuf Reflection Service for gRPC"
optional = false
python-versions = ">=3.6"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "grpcio-reflection-1.62.3.tar.gz", hash = "sha256:cb84682933c400bddf94dd94f928d1c6570f500b6dd255973d4bfb495b82585f"},
{file = "grpcio_reflection-1.62.3-py3-none-any.whl", hash = "sha256:a48ef37df81a3bada78261fc92ef382f061112f989d1312398b945cc69838b9c"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
grpcio = ">=1.62.3"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
protobuf = ">=4.21.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "grpcio-status"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Status proto mapping for gRPC"
optional = false
python-versions = ">=3.6"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "grpcio-status-1.62.3.tar.gz", hash = "sha256:289bdd7b2459794a12cf95dc0cb727bd4a1742c37bd823f760236c937e53a485"},
{file = "grpcio_status-1.62.3-py3-none-any.whl", hash = "sha256:f9049b762ba8de6b1086789d8315846e094edac2c50beaf462338b301a8fd4b8"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
googleapis-common-protos = ">=1.5.5"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
grpcio = ">=1.62.3"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
protobuf = ">=4.21.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "grpcio-tools"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "1.62.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Protobuf code generator for gRPC"
optional = false
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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[package.dependencies]
grpcio = ">=1.62.3"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
protobuf = ">=4.21.6,<5.0dev"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
setuptools = "*"
[[package]]
name = "hf-transfer"
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 15:18:54 +00:00
version = "0.1.8"
description = "Speed up file transfers with the Hugging Face Hub."
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
optional = false
python-versions = ">=3.7"
files = [
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 15:18:54 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "huggingface-hub"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "0.26.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
optional = false
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
python-versions = ">=3.8.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "huggingface_hub-0.26.1-py3-none-any.whl", hash = "sha256:5927a8fc64ae68859cd954b7cc29d1c8390a5e15caba6d3d349c973be8fdacf3"},
{file = "huggingface_hub-0.26.1.tar.gz", hash = "sha256:414c0d9b769eecc86c70f9d939d0f48bb28e8461dd1130021542eff0212db890"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
filelock = "*"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
fsspec = ">=2023.5.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
packaging = ">=20.9"
pyyaml = ">=5.1"
requests = "*"
tqdm = ">=4.42.1"
typing-extensions = ">=3.7.4.3"
[package.extras]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "libcst (==1.4.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
cli = ["InquirerPy (==0.3.4)"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "libcst (==1.4.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
hf-transfer = ["hf-transfer (>=0.1.4)"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
inference = ["aiohttp"]
quality = ["libcst (==1.4.0)", "mypy (==1.5.1)", "ruff (>=0.5.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
tensorflow = ["graphviz", "pydot", "tensorflow"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
tensorflow-testing = ["keras (<3.0)", "tensorflow"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
torch = ["safetensors[torch]", "torch"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "idna"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "3.10"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Internationalized Domain Names in Applications (IDNA)"
optional = false
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
python-versions = ">=3.6"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"},
{file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"},
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
[package.extras]
all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
[[package]]
name = "importlib-metadata"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "8.5.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
description = "Read metadata from Python packages"
optional = false
python-versions = ">=3.8"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "importlib_metadata-8.5.0-py3-none-any.whl", hash = "sha256:45e54197d28b7a7f1559e60b95e7c567032b602131fbd588f1497f47880aa68b"},
{file = "importlib_metadata-8.5.0.tar.gz", hash = "sha256:71522656f0abace1d072b9e5481a48f07c138e00f079c38c8f883823f9c26bd7"},
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
]
[package.dependencies]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
zipp = ">=3.20"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
[package.extras]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
cover = ["pytest-cov"]
Update to SynapseAI 1.16.0 (#167) Co-authored-by: Alexey Fadeev <alexey.fadeev@intel.com>
2024-07-03 09:08:56 +00:00
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
enabler = ["pytest-enabler (>=2.2)"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
perf = ["ipython"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
type = ["pytest-mypy"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "iniconfig"
version = "2.0.0"
description = "brain-dead simple config-ini parsing"
optional = false
python-versions = ">=3.7"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
{file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
{file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "interegular"
version = "0.3.3"
description = "a regex intersection checker"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.7"
files = [
{file = "interegular-0.3.3-py37-none-any.whl", hash = "sha256:b0c07007d48c89d6d19f7204972d369b2a77222722e126b6aa63aa721dc3b19c"},
{file = "interegular-0.3.3.tar.gz", hash = "sha256:d9b697b21b34884711399ba0f0376914b81899ce670032486d0d048344a76600"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 19:54:39 +00:00
name = "jinja2"
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
version = "3.1.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "A very fast and expressive template engine."
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=3.7"
files = [
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
{file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
{file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
MarkupSafe = ">=2.0"
[package.extras]
i18n = ["Babel (>=2.7)"]
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "joblib"
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
version = "1.4.2"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "Lightweight pipelining with Python functions"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.8"
files = [
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
{file = "joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6"},
{file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"},
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[[package]]
name = "jsonschema"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
version = "4.23.0"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "An implementation of JSON Schema validation for Python"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.8"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
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{file = "jsonschema-4.23.0.tar.gz", hash = "sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4"},
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
attrs = ">=22.2.0"
jsonschema-specifications = ">=2023.03.6"
referencing = ">=0.28.4"
rpds-py = ">=0.7.1"
[package.extras]
format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=24.6.0)"]
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "jsonschema-specifications"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "2024.10.1"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
python-versions = ">=3.9"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
referencing = ">=0.31.0"
[[package]]
name = "lark"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "1.2.2"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "a modern parsing library"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
python-versions = ">=3.8"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.extras]
atomic-cache = ["atomicwrites"]
interegular = ["interegular (>=0.3.1,<0.4.0)"]
nearley = ["js2py"]
regex = ["regex"]
[[package]]
name = "llvmlite"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
version = "0.43.0"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "lightweight wrapper around basic LLVM functionality"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.9"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "loguru"
version = "0.6.0"
description = "Python logging made (stupidly) simple"
optional = false
python-versions = ">=3.5"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
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{file = "loguru-0.6.0.tar.gz", hash = "sha256:066bd06758d0a513e9836fd9c6b5a75bfb3fd36841f4b996bc60b547a309d41c"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
colorama = {version = ">=0.3.4", markers = "sys_platform == \"win32\""}
win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""}
[package.extras]
dev = ["Sphinx (>=4.1.1)", "black (>=19.10b0)", "colorama (>=0.3.4)", "docutils (==0.16)", "flake8 (>=3.7.7)", "isort (>=5.1.1)", "pytest (>=4.6.2)", "pytest-cov (>=2.7.1)", "sphinx-autobuild (>=0.7.1)", "sphinx-rtd-theme (>=0.4.3)", "tox (>=3.9.0)"]
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
[[package]]
name = "markdown-it-py"
version = "3.0.0"
description = "Python port of markdown-it. Markdown parsing, done right!"
optional = false
python-versions = ">=3.8"
files = [
{file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"},
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]
[package.dependencies]
mdurl = ">=0.1,<1.0"
[package.extras]
benchmarking = ["psutil", "pytest", "pytest-benchmark"]
code-style = ["pre-commit (>=3.0,<4.0)"]
compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
linkify = ["linkify-it-py (>=1,<3)"]
plugins = ["mdit-py-plugins"]
profiling = ["gprof2dot"]
rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 19:54:39 +00:00
name = "markupsafe"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "3.0.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Safely add untrusted strings to HTML/XML markup."
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
optional = false
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
python-versions = ">=3.9"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Install Marlin from standalone package (#2320)
2024-07-29 13:37:10 +00:00
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp310-cp310-linux_x86_64.whl", hash = "sha256:9a5afcf19b0f5917e43353cc19873fb3c4d4d0b924e2a95a37884f9ce208d0bd"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp310-cp310-linux_x86_64.whl"
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp311-cp311-linux_x86_64.whl", hash = "sha256:1e64fcc7ebadfaffa60091ee9201ae3daaf5c1be3be60c8c054143a3dcb72d5d"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp311-cp311-linux_x86_64.whl"
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp312-cp312-linux_x86_64.whl", hash = "sha256:e75f3ce9b1c13a4ed43a380d88e1d34d297259452db037ec1973ec33dc2eb78e"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp312-cp312-linux_x86_64.whl"
[[package]]
name = "marlin-kernels"
version = "0.2.0"
description = "Marlin quantization kernels"
optional = true
python-versions = ">=3.7"
files = [
{file = "marlin_kernels-0.2.0+cu123torch2.4-cp39-cp39-linux_x86_64.whl", hash = "sha256:2f99a27f70b391887ee6adffeeee7c3f4df7fac37393f9fb16d4cace2b3f6457"},
]
[package.dependencies]
torch = "*"
[package.source]
type = "url"
url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp39-cp39-linux_x86_64.whl"
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
[[package]]
name = "mdurl"
version = "0.1.2"
description = "Markdown URL utilities"
optional = false
python-versions = ">=3.7"
files = [
{file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"},
{file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
]
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
[[package]]
name = "moe-kernels"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
version = "0.4.0"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
description = "MoE kernels"
optional = true
python-versions = ">=3.7"
files = [
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
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Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
]
[package.dependencies]
nvidia-ml-py = "*"
torch = "*"
triton = "*"
[package.source]
type = "url"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
url = "https://github.com/danieldk/moe-kernels/releases/download/v0.4.0/moe_kernels-0.4.0+cu123torch2.4-cp310-cp310-linux_x86_64.whl"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
[[package]]
name = "moe-kernels"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
version = "0.4.0"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
description = "MoE kernels"
optional = true
python-versions = ">=3.7"
files = [
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
{file = "moe_kernels-0.4.0+cu123torch2.4-cp311-cp311-linux_x86_64.whl", hash = "sha256:8ca72a064ceb84a23a3437cc6e6363907ad41588877f6acb1febc010fc7beb22"},
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
]
[package.dependencies]
nvidia-ml-py = "*"
torch = "*"
triton = "*"
[package.source]
type = "url"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
url = "https://github.com/danieldk/moe-kernels/releases/download/v0.4.0/moe_kernels-0.4.0+cu123torch2.4-cp311-cp311-linux_x86_64.whl"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
[[package]]
name = "moe-kernels"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
version = "0.4.0"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
description = "MoE kernels"
optional = true
python-versions = ">=3.7"
files = [
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
{file = "moe_kernels-0.4.0+cu123torch2.4-cp312-cp312-linux_x86_64.whl", hash = "sha256:d302d6b16bb4905b2312dc68da6a6f51e87d0cd3c4bf1f23d995501162399a8e"},
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
]
[package.dependencies]
nvidia-ml-py = "*"
torch = "*"
triton = "*"
[package.source]
type = "url"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
url = "https://github.com/danieldk/moe-kernels/releases/download/v0.4.0/moe_kernels-0.4.0+cu123torch2.4-cp312-cp312-linux_x86_64.whl"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
[[package]]
name = "moe-kernels"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
version = "0.4.0"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
description = "MoE kernels"
optional = true
python-versions = ">=3.7"
files = [
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
{file = "moe_kernels-0.4.0+cu123torch2.4-cp39-cp39-linux_x86_64.whl", hash = "sha256:6aee3e723efa5113c338b40e6cb20fa62da6c442c65c1a6cc97751d34158a93a"},
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
]
[package.dependencies]
nvidia-ml-py = "*"
torch = "*"
triton = "*"
[package.source]
type = "url"
Add support for GPTQ-quantized MoE models using MoE Marlin (#2557) This change add support for MoE models that use GPTQ quantization. Currently only models with the following properties are supported: - No `desc_act` with tensor parallelism, unless `group_size=-1`. - No asymmetric quantization. - No AWQ.
2024-09-30 09:14:32 +00:00
url = "https://github.com/danieldk/moe-kernels/releases/download/v0.4.0/moe_kernels-0.4.0+cu123torch2.4-cp39-cp39-linux_x86_64.whl"
Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "mpmath"
version = "1.3.0"
description = "Python library for arbitrary-precision floating-point arithmetic"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = "*"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
{file = "mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c"},
{file = "mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
develop = ["codecov", "pycodestyle", "pytest (>=4.6)", "pytest-cov", "wheel"]
docs = ["sphinx"]
gmpy = ["gmpy2 (>=2.1.0a4)"]
tests = ["pytest (>=4.6)"]
[[package]]
name = "multidict"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "6.1.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "multidict implementation"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
optional = false
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
[package.dependencies]
typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""}
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "multiprocess"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "0.70.15"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "better multiprocessing and multithreading in Python"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
optional = false
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
dill = ">=0.3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
[[package]]
name = "nest-asyncio"
version = "1.6.0"
description = "Patch asyncio to allow nested event loops"
optional = true
python-versions = ">=3.5"
files = [
{file = "nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c"},
{file = "nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe"},
]
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "networkx"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
version = "3.2.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Python package for creating and manipulating graphs and networks"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3.9"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
default = ["matplotlib (>=3.5)", "numpy (>=1.22)", "pandas (>=1.4)", "scipy (>=1.9,!=1.11.0,!=1.11.1)"]
developer = ["changelist (==0.4)", "mypy (>=1.1)", "pre-commit (>=3.2)", "rtoml"]
doc = ["nb2plots (>=0.7)", "nbconvert (<7.9)", "numpydoc (>=1.6)", "pillow (>=9.4)", "pydata-sphinx-theme (>=0.14)", "sphinx (>=7)", "sphinx-gallery (>=0.14)", "texext (>=0.6.7)"]
extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.11)", "sympy (>=1.10)"]
test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "numba"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
version = "0.60.0"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "compiling Python code using LLVM"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.9"
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
llvmlite = "==0.43.*"
numpy = ">=1.22,<2.1"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
[[package]]
name = "numpy"
hotfix: pin numpy (#2289)
2024-07-23 15:53:19 +00:00
version = "1.26.4"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
description = "Fundamental package for array computing in Python"
optional = false
python-versions = ">=3.9"
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hotfix: pin numpy (#2289)
2024-07-23 15:53:19 +00:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
]
[[package]]
name = "nvidia-cublas-cu12"
version = "12.1.3.1"
description = "CUBLAS native runtime libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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[[package]]
name = "nvidia-cuda-cupti-cu12"
version = "12.1.105"
description = "CUDA profiling tools runtime libs."
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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[[package]]
name = "nvidia-cuda-nvrtc-cu12"
version = "12.1.105"
description = "NVRTC native runtime libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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version = "12.1.105"
description = "CUDA Runtime native Libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 11:34:44 +00:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
description = "cuDNN runtime libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 11:34:44 +00:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
]
[package.dependencies]
nvidia-cublas-cu12 = "*"
[[package]]
name = "nvidia-cufft-cu12"
version = "11.0.2.54"
description = "CUFFT native runtime libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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version = "10.3.2.106"
description = "CURAND native runtime libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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version = "11.4.5.107"
description = "CUDA solver native runtime libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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nvidia-cusparse-cu12 = "*"
nvidia-nvjitlink-cu12 = "*"
[[package]]
name = "nvidia-cusparse-cu12"
version = "12.1.0.106"
description = "CUSPARSE native runtime libraries"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
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Move to moe-kernels package and switch to common MoE layer (#2511) * Move to moe-kernels package and switch to common MoE layer This change introduces the new `moe-kernels` package: - Add `moe-kernels` as a dependency. - Introduce a `SparseMoELayer` module that can be used by MoE models. - Port over Mixtral and Deepseek. * Make `cargo check` pass * Update runner
2024-09-17 16:08:58 +00:00
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python-versions = "*"
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
[[package]]
name = "nvidia-nccl-cu12"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
version = "2.20.5"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
description = "NVIDIA Collective Communication Library (NCCL) Runtime"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
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{file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56"},
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
]
[[package]]
name = "nvidia-nvjitlink-cu12"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "12.6.77"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
description = "Nvidia JIT LTO Library"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "nvidia_nvjitlink_cu12-12.6.77-py3-none-manylinux2014_aarch64.whl", hash = "sha256:3bf10d85bb1801e9c894c6e197e44dd137d2a0a9e43f8450e9ad13f2df0dd52d"},
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{file = "nvidia_nvjitlink_cu12-12.6.77-py3-none-win_amd64.whl", hash = "sha256:410718cd44962bed862a31dd0318620f6f9a8b28a6291967bcfcb446a6516771"},
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
]
[[package]]
name = "nvidia-nvtx-cu12"
version = "12.1.105"
description = "NVIDIA Tools Extension"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3"
files = [
{file = "nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:dc21cf308ca5691e7c04d962e213f8a4aa9bbfa23d95412f452254c2caeb09e5"},
{file = "nvidia_nvtx_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:65f4d98982b31b60026e0e6de73fbdfc09d08a96f4656dd3665ca616a11e1e82"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "opentelemetry-api"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry Python API"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_api-1.25.0-py3-none-any.whl", hash = "sha256:757fa1aa020a0f8fa139f8959e53dec2051cc26b832e76fa839a6d76ecefd737"},
{file = "opentelemetry_api-1.25.0.tar.gz", hash = "sha256:77c4985f62f2614e42ce77ee4c9da5fa5f0bc1e1821085e9a47533a9323ae869"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
deprecated = ">=1.2.6"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
importlib-metadata = ">=6.0,<=7.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "opentelemetry-exporter-otlp"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry Collector Exporters"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
files = [
{file = "opentelemetry_exporter_otlp-1.25.0-py3-none-any.whl", hash = "sha256:d67a831757014a3bc3174e4cd629ae1493b7ba8d189e8a007003cacb9f1a6b60"},
{file = "opentelemetry_exporter_otlp-1.25.0.tar.gz", hash = "sha256:ce03199c1680a845f82e12c0a6a8f61036048c07ec7a0bd943142aca8fa6ced0"},
]
[package.dependencies]
opentelemetry-exporter-otlp-proto-grpc = "1.25.0"
opentelemetry-exporter-otlp-proto-http = "1.25.0"
[[package]]
name = "opentelemetry-exporter-otlp-proto-common"
version = "1.25.0"
description = "OpenTelemetry Protobuf encoding"
optional = false
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_exporter_otlp_proto_common-1.25.0-py3-none-any.whl", hash = "sha256:15637b7d580c2675f70246563363775b4e6de947871e01d0f4e3881d1848d693"},
{file = "opentelemetry_exporter_otlp_proto_common-1.25.0.tar.gz", hash = "sha256:c93f4e30da4eee02bacd1e004eb82ce4da143a2f8e15b987a9f603e0a85407d3"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
opentelemetry-proto = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "opentelemetry-exporter-otlp-proto-grpc"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_exporter_otlp_proto_grpc-1.25.0-py3-none-any.whl", hash = "sha256:3131028f0c0a155a64c430ca600fd658e8e37043cb13209f0109db5c1a3e4eb4"},
{file = "opentelemetry_exporter_otlp_proto_grpc-1.25.0.tar.gz", hash = "sha256:c0b1661415acec5af87625587efa1ccab68b873745ca0ee96b69bb1042087eac"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
deprecated = ">=1.2.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
googleapis-common-protos = ">=1.52,<2.0"
grpcio = ">=1.0.0,<2.0.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
opentelemetry-api = ">=1.15,<2.0"
opentelemetry-exporter-otlp-proto-common = "1.25.0"
opentelemetry-proto = "1.25.0"
opentelemetry-sdk = ">=1.25.0,<1.26.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "opentelemetry-exporter-otlp-proto-http"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry Collector Protobuf over HTTP Exporter"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_exporter_otlp_proto_http-1.25.0-py3-none-any.whl", hash = "sha256:2eca686ee11b27acd28198b3ea5e5863a53d1266b91cda47c839d95d5e0541a6"},
{file = "opentelemetry_exporter_otlp_proto_http-1.25.0.tar.gz", hash = "sha256:9f8723859e37c75183ea7afa73a3542f01d0fd274a5b97487ea24cb683d7d684"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
deprecated = ">=1.2.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
googleapis-common-protos = ">=1.52,<2.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
opentelemetry-api = ">=1.15,<2.0"
opentelemetry-exporter-otlp-proto-common = "1.25.0"
opentelemetry-proto = "1.25.0"
opentelemetry-sdk = ">=1.25.0,<1.26.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
requests = ">=2.7,<3.0"
[[package]]
name = "opentelemetry-instrumentation"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_instrumentation-0.46b0-py3-none-any.whl", hash = "sha256:89cd721b9c18c014ca848ccd11181e6b3fd3f6c7669e35d59c48dc527408c18b"},
{file = "opentelemetry_instrumentation-0.46b0.tar.gz", hash = "sha256:974e0888fb2a1e01c38fbacc9483d024bb1132aad92d6d24e2e5543887a7adda"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
opentelemetry-api = ">=1.4,<2.0"
setuptools = ">=16.0"
wrapt = ">=1.0.0,<2.0.0"
[[package]]
name = "opentelemetry-instrumentation-grpc"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry gRPC instrumentation"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_instrumentation_grpc-0.46b0-py3-none-any.whl", hash = "sha256:cccfb28db07c28849709f2dcf330237fae0fca9f86971bfce27b28bb9a8b0577"},
{file = "opentelemetry_instrumentation_grpc-0.46b0.tar.gz", hash = "sha256:9c5738592cf82672805099826b676d352324b54e03f9ac72a1368ba0605d6ff9"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
opentelemetry-api = ">=1.12,<2.0"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
opentelemetry-instrumentation = "0.46b0"
opentelemetry-semantic-conventions = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
wrapt = ">=1.0.0,<2.0.0"
[package.extras]
instruments = ["grpcio (>=1.27,<2.0)"]
[[package]]
name = "opentelemetry-proto"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry Python Proto"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_proto-1.25.0-py3-none-any.whl", hash = "sha256:f07e3341c78d835d9b86665903b199893befa5e98866f63d22b00d0b7ca4972f"},
{file = "opentelemetry_proto-1.25.0.tar.gz", hash = "sha256:35b6ef9dc4a9f7853ecc5006738ad40443701e52c26099e197895cbda8b815a3"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
protobuf = ">=3.19,<5.0"
[[package]]
name = "opentelemetry-sdk"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "1.25.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry Python SDK"
optional = false
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "opentelemetry_sdk-1.25.0-py3-none-any.whl", hash = "sha256:d97ff7ec4b351692e9d5a15af570c693b8715ad78b8aafbec5c7100fe966b4c9"},
{file = "opentelemetry_sdk-1.25.0.tar.gz", hash = "sha256:ce7fc319c57707ef5bf8b74fb9f8ebdb8bfafbe11898410e0d2a761d08a98ec7"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
opentelemetry-api = "1.25.0"
opentelemetry-semantic-conventions = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
typing-extensions = ">=3.7.4"
[[package]]
name = "opentelemetry-semantic-conventions"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "0.46b0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "OpenTelemetry Semantic Conventions"
optional = false
python-versions = ">=3.7"
files = [
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
{file = "opentelemetry_semantic_conventions-0.36b0-py3-none-any.whl", hash = "sha256:adc05635e87b9d3e007c9f530eed487fc3ef2177d02f82f674f28ebf9aff8243"},
{file = "opentelemetry_semantic_conventions-0.36b0.tar.gz", hash = "sha256:829dc221795467d98b773c04096e29be038d77526dc8d6ac76f546fb6279bf01"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
[[package]]
name = "optimum"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "1.23.2"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
description = "Optimum Library is an extension of the Hugging Face Transformers library, providing a framework to integrate third-party libraries from Hardware Partners and interface with their specific functionality."
optional = false
python-versions = ">=3.7.0"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "optimum-1.23.2-py3-none-any.whl", hash = "sha256:1b6f450b2c0203377b76cf4dd1e05e45b116d8069612fe2ad73df8b5743d5a57"},
{file = "optimum-1.23.2.tar.gz", hash = "sha256:245415add6e621c6c5b7c29eee968bc325fc1a982d9c42eb83d97b7ec844ef39"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
[package.dependencies]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
coloredlogs = "*"
datasets = "*"
huggingface-hub = ">=0.8.0"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
numpy = "*"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
packaging = "*"
sympy = "*"
torch = ">=1.11"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
transformers = {version = ">=4.29", extras = ["sentencepiece"]}
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
[package.extras]
amd = ["optimum-amd"]
benchmark = ["evaluate (>=0.2.0)", "optuna", "scikit-learn", "seqeval", "torchvision", "tqdm"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
dev = ["Pillow", "accelerate", "black (>=23.1,<24.0)", "diffusers (>=0.17.0)", "einops", "invisible-watermark", "parameterized", "pytest (<=8.0.0)", "pytest-xdist", "requests", "rjieba", "ruff (==0.1.5)", "sacremoses", "scikit-learn", "timm", "torchaudio", "torchvision"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
diffusers = ["diffusers"]
doc-build = ["accelerate"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
exporters = ["onnx", "onnxruntime", "timm", "transformers (<4.46.0)"]
exporters-gpu = ["onnx", "onnxruntime-gpu", "timm", "transformers (<4.46.0)"]
exporters-tf = ["datasets (<=2.16)", "h5py", "numpy (<1.24.0)", "onnx", "onnxruntime", "tensorflow (>=2.4,<=2.12.1)", "tf2onnx", "timm", "transformers[sentencepiece] (>=4.26,<4.38)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
furiosa = ["optimum-furiosa"]
graphcore = ["optimum-graphcore"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
habana = ["optimum-habana", "transformers (>=4.45.0,<4.46.0)"]
Upgrade to 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-07-17 05:08:52 +00:00
intel = ["optimum-intel (>=1.18.0)"]
ipex = ["optimum-intel[ipex] (>=1.18.0)"]
neural-compressor = ["optimum-intel[neural-compressor] (>=1.18.0)"]
(chore): torch 2.3.0 (#1833) <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 16:15:35 +00:00
neuron = ["optimum-neuron[neuron] (>=0.0.20)", "transformers (>=4.36.2,<4.42.0)"]
neuronx = ["optimum-neuron[neuronx] (>=0.0.20)", "transformers (>=4.36.2,<4.42.0)"]
Upgrade to 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-07-17 05:08:52 +00:00
nncf = ["optimum-intel[nncf] (>=1.18.0)"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
onnxruntime = ["datasets (>=1.2.1)", "evaluate", "onnx", "onnxruntime (>=1.11.0)", "protobuf (>=3.20.1)", "transformers (<4.46.0)"]
onnxruntime-gpu = ["accelerate", "datasets (>=1.2.1)", "evaluate", "onnx", "onnxruntime-gpu (>=1.11.0)", "protobuf (>=3.20.1)", "transformers (<4.46.0)"]
Upgrade to 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-07-17 05:08:52 +00:00
openvino = ["optimum-intel[openvino] (>=1.18.0)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
quality = ["black (>=23.1,<24.0)", "ruff (==0.1.5)"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
quanto = ["optimum-quanto (>=0.2.4)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
tests = ["Pillow", "accelerate", "diffusers (>=0.17.0)", "einops", "invisible-watermark", "parameterized", "pytest (<=8.0.0)", "pytest-xdist", "requests", "rjieba", "sacremoses", "scikit-learn", "timm", "torchaudio", "torchvision"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
[[package]]
name = "optimum-habana"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "1.14.1"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
description = "Optimum Habana is the interface between the Hugging Face Transformers and Diffusers libraries and Habana's Gaudi processor (HPU). It provides a set of tools enabling easy model loading, training and inference on single- and multi-HPU settings for different downstream tasks."
optional = false
python-versions = "*"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "optimum_habana-1.14.1-py3-none-any.whl", hash = "sha256:557dd06a5fa2597b1487384a354c3a1618390c35e6b088f5d7a80c0611fe2bfd"},
{file = "optimum_habana-1.14.1.tar.gz", hash = "sha256:627626860b82452b75f73087df3e14004278ed30dacf767c100f1324675c8120"},
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
]
[package.dependencies]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
accelerate = ">=0.33.0,<0.34.0"
diffusers = "0.29.2"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
huggingface-hub = ">=0.24.7"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
optimum = "*"
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
sentence-transformers = {version = "3.0.1", extras = ["train"]}
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
torch = "*"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
transformers = ">=4.45.2,<4.46.0"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
[package.extras]
quality = ["hf-doc-builder", "ruff"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
tests = ["GitPython", "datasets", "optuna", "parameterized", "peft", "psutil", "pytest (<8.0.0)", "safetensors", "scipy", "sentencepiece", "timm", "torchsde"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "outlines"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "0.0.34"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "Probabilistic Generative Model Programming"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.8"
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
{file = "outlines-0.0.34-py3-none-any.whl", hash = "sha256:911588a7e64a4f193b97fb4c501d98ccfd4e95a98f6a3ada67a280bf0c373c50"},
{file = "outlines-0.0.34.tar.gz", hash = "sha256:594e7204c770b47a62eb5c2ba7d25ea0ab2e16882b5f04556712a0228d3d3309"},
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
cloudpickle = "*"
diskcache = "*"
interegular = "*"
jinja2 = "*"
joblib = "*"
jsonschema = "*"
lark = "*"
nest-asyncio = "*"
numba = "*"
numpy = "*"
pydantic = ">=2.0"
referencing = "*"
requests = "*"
scipy = "*"
torch = ">=2.1.0"
transformers = "*"
[package.extras]
serve = ["fastapi", "pydantic (>=2.0)", "ray (==2.9.0)", "uvicorn", "vllm (>=0.3.0)"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
test = ["accelerate", "beartype (<0.16.0)", "coverage[toml] (>=5.1)", "datasets", "diff-cover", "huggingface-hub", "llama-cpp-python (>=0.2.42)", "pre-commit", "pytest", "pytest-benchmark", "pytest-cov", "pytest-mock", "responses", "transformers"]
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "packaging"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
version = "24.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Core utilities for Python packages"
optional = false
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
{file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"},
{file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "pandas"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2.2.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Powerful data structures for data analysis, time series, and statistics"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 13:31:27 +00:00
python-versions = ">=3.9"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
numpy = [
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
]
python-dateutil = ">=2.8.2"
pytz = ">=2020.1"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
tzdata = ">=2022.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
all = ["PyQt5 (>=5.15.9)", "SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)", "beautifulsoup4 (>=4.11.2)", "bottleneck (>=1.3.6)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=2022.12.0)", "fsspec (>=2022.11.0)", "gcsfs (>=2022.11.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.9.2)", "matplotlib (>=3.6.3)", "numba (>=0.56.4)", "numexpr (>=2.8.4)", "odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "pandas-gbq (>=0.19.0)", "psycopg2 (>=2.9.6)", "pyarrow (>=10.0.1)", "pymysql (>=1.0.2)", "pyreadstat (>=1.2.0)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "qtpy (>=2.3.0)", "s3fs (>=2022.11.0)", "scipy (>=1.10.0)", "tables (>=3.8.0)", "tabulate (>=0.9.0)", "xarray (>=2022.12.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)", "zstandard (>=0.19.0)"]
aws = ["s3fs (>=2022.11.0)"]
clipboard = ["PyQt5 (>=5.15.9)", "qtpy (>=2.3.0)"]
compression = ["zstandard (>=0.19.0)"]
computation = ["scipy (>=1.10.0)", "xarray (>=2022.12.0)"]
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 13:31:27 +00:00
consortium-standard = ["dataframe-api-compat (>=0.1.7)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)"]
feather = ["pyarrow (>=10.0.1)"]
fss = ["fsspec (>=2022.11.0)"]
gcp = ["gcsfs (>=2022.11.0)", "pandas-gbq (>=0.19.0)"]
hdf5 = ["tables (>=3.8.0)"]
html = ["beautifulsoup4 (>=4.11.2)", "html5lib (>=1.1)", "lxml (>=4.9.2)"]
mysql = ["SQLAlchemy (>=2.0.0)", "pymysql (>=1.0.2)"]
output-formatting = ["jinja2 (>=3.1.2)", "tabulate (>=0.9.0)"]
parquet = ["pyarrow (>=10.0.1)"]
performance = ["bottleneck (>=1.3.6)", "numba (>=0.56.4)", "numexpr (>=2.8.4)"]
plot = ["matplotlib (>=3.6.3)"]
postgresql = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "psycopg2 (>=2.9.6)"]
pyarrow = ["pyarrow (>=10.0.1)"]
spss = ["pyreadstat (>=1.2.0)"]
sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)"]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
xml = ["lxml (>=4.9.2)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "peft"
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
version = "0.10.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Parameter-Efficient Fine-Tuning (PEFT)"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=3.8.0"
files = [
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
{file = "peft-0.10.0-py3-none-any.whl", hash = "sha256:d5249c97e818d3e31f92553c73c2953acd0ec12649b8b749afff7152cbc86cbb"},
{file = "peft-0.10.0.tar.gz", hash = "sha256:36a7628c15f88d37abb26cfc74c22468f9037ee02e9c9b65de943cfe7c672049"},
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
]
[package.dependencies]
Update to peft 0.8.2 (#1537) <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> - [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [x] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [x] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [x] Did you write any new necessary tests? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. @OlivierDehaene OR @Narsil
2024-02-08 11:44:04 +00:00
accelerate = ">=0.21.0"
huggingface-hub = ">=0.17.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
numpy = ">=1.17"
packaging = ">=20.0"
psutil = "*"
pyyaml = "*"
safetensors = "*"
torch = ">=1.13.0"
Update to peft 0.8.2 (#1537) <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> - [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [x] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [x] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [x] Did you write any new necessary tests? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. @OlivierDehaene OR @Narsil
2024-02-08 11:44:04 +00:00
tqdm = "*"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
transformers = "*"
[package.extras]
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
dev = ["black", "hf-doc-builder", "ruff (>=0.2.1,<0.3.0)"]
docs-specific = ["black", "hf-doc-builder"]
quality = ["black", "hf-doc-builder", "ruff (>=0.2.1,<0.3.0)"]
test = ["black", "datasets", "diffusers (<0.21.0)", "hf-doc-builder", "parameterized", "pytest", "pytest-cov", "pytest-xdist", "ruff (>=0.2.1,<0.3.0)", "scipy"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
[[package]]
name = "pillow"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "11.0.0"
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
description = "Python Imaging Library (Fork)"
optional = false
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
python-versions = ">=3.9"
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
]
[package.extras]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
docs = ["furo", "olefile", "sphinx (>=8.1)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
fpx = ["olefile"]
mic = ["olefile"]
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
typing = ["typing-extensions"]
xmp = ["defusedxml"]
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "pluggy"
v1.4.0 (#1494)
2024-01-26 18:04:57 +00:00
version = "1.5.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "plugin and hook calling mechanisms for python"
optional = false
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 12:28:22 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
v1.4.0 (#1494)
2024-01-26 18:04:57 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
dev = ["pre-commit", "tox"]
testing = ["pytest", "pytest-benchmark"]
(chore): torch 2.3.0 (#1833) <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 16:15:35 +00:00
[[package]]
name = "prometheus-client"
version = "0.20.0"
description = "Python client for the Prometheus monitoring system."
optional = false
python-versions = ">=3.8"
files = [
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[package.extras]
twisted = ["twisted"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "protobuf"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "4.25.5"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
description = ""
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
optional = false
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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feat(server): use latest flash attention commit (#543) @njhill FYI
2023-07-04 18:23:55 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "psutil"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "6.1.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Cross-platform lib for process and system monitoring in Python."
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438) Let's start discussing implementation. - Need to expose the quantization scripts (either included here or add doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa) - Make sure GPTQ works for multiple models (priority to Falcon). Currently it means that every place we use `get_{tensor|sharded}` to check for quantization. My idea is to reintegrate as much as possible into `utils/layer.py` by expanding `load_multi` to be a bit more generic. This might require some thinking, but ultimately the `qweight,qzeros,scales,g_idx` should be in a single place, and independant of bias presence. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 10:27:01 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
dev = ["black", "check-manifest", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pytest-cov", "requests", "rstcheck", "ruff", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "virtualenv", "wheel"]
test = ["pytest", "pytest-xdist", "setuptools"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
(chore): torch 2.3.0 (#1833) <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-30 16:15:35 +00:00
[[package]]
name = "py-cpuinfo"
version = "9.0.0"
description = "Get CPU info with pure Python"
optional = false
python-versions = "*"
files = [
{file = "py-cpuinfo-9.0.0.tar.gz", hash = "sha256:3cdbbf3fac90dc6f118bfd64384f309edeadd902d7c8fb17f02ffa1fc3f49690"},
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]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "pyarrow"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
version = "17.0.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Python library for Apache Arrow"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 12:28:22 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
v1.4.0 (#1494)
2024-01-26 18:04:57 +00:00
numpy = ">=1.16.6"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
[package.extras]
test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "pydantic"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2.9.2"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "Data validation using Python type hints"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.8"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
annotated-types = ">=0.6.0"
pydantic-core = "2.23.4"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
typing-extensions = {version = ">=4.6.1", markers = "python_version < \"3.13\""}
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[package.extras]
email = ["email-validator (>=2.0.0)"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
timezone = ["tzdata"]
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "pydantic-core"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2.23.4"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "Core functionality for Pydantic validation and serialization"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.8"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
[[package]]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
name = "pyreadline3"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "3.5.4"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
description = "A python implementation of GNU readline."
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
optional = false
python-versions = ">=3.8"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
]
[package.extras]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
dev = ["build", "flake8", "mypy", "pytest", "twine"]
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "pytest"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
version = "7.4.4"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "pytest: simple powerful testing with Python"
optional = false
python-versions = ">=3.7"
files = [
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
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feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438) Let's start discussing implementation. - Need to expose the quantization scripts (either included here or add doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa) - Make sure GPTQ works for multiple models (priority to Falcon). Currently it means that every place we use `get_{tensor|sharded}` to check for quantization. My idea is to reintegrate as much as possible into `utils/layer.py` by expanding `load_multi` to be a bit more generic. This might require some thinking, but ultimately the `qweight,qzeros,scales,g_idx` should be in a single place, and independant of bias presence. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 10:27:01 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
colorama = {version = "*", markers = "sys_platform == \"win32\""}
exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
iniconfig = "*"
packaging = "*"
pluggy = ">=0.12,<2.0"
tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
[package.extras]
testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
[[package]]
name = "python-dateutil"
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
version = "2.9.0.post0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Extensions to the standard Python datetime module"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
files = [
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
{file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"},
{file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"},
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
six = ">=1.5"
[[package]]
name = "pytz"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2024.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "World timezone definitions, modern and historical"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = "*"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "pytz-2024.2-py2.py3-none-any.whl", hash = "sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725"},
{file = "pytz-2024.2.tar.gz", hash = "sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a"},
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 19:54:39 +00:00
name = "pyyaml"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "6.0.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "YAML parser and emitter for Python"
optional = false
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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Init
2022-10-08 10:30:12 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "referencing"
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
version = "0.35.1"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "JSON Referencing + Python"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
optional = true
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.8"
files = [
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
attrs = ">=22.2.0"
rpds-py = ">=0.7.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "regex"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2024.9.11"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Alternative regular expression module, to replace re."
optional = false
Update peft version to 0.10.0 (#141) Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-14 11:49:55 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438) Let's start discussing implementation. - Need to expose the quantization scripts (either included here or add doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa) - Make sure GPTQ works for multiple models (priority to Falcon). Currently it means that every place we use `get_{tensor|sharded}` to check for quantization. My idea is to reintegrate as much as possible into `utils/layer.py` by expanding `load_multi` to be a bit more generic. This might require some thinking, but ultimately the `qweight,qzeros,scales,g_idx` should be in a single place, and independant of bias presence. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 10:27:01 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "requests"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
version = "2.32.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Python HTTP for Humans."
optional = false
Upgrading all versions. (#1759)
2024-04-18 15:17:40 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
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feat: add distributed tracing (#62)
2023-02-13 12:02:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
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Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
[[package]]
name = "rich"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "13.8.1"
Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
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Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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Fixing exl2 and other quanize tests again. (#2419) * Fixing exl2 and other quanize tests again. * Mark exl2 as non release (so CI tests them, needs to be removed latet). * Fixing exl2 (by disabling cuda graphs) * Fix quantization defaults without cuda graphs on exl2 (linked to new issues with it). * Removing serde override. * Go back to released exl2 and remove log. * Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 09:12:51 +00:00
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v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
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name = "rpds-py"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
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Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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v1.4.1 (#1568)
2024-02-16 16:50:57 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "safetensors"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "0.4.5"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
description = ""
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
optional = false
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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feat(server): Improved doc
2022-11-07 11:53:56 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
all = ["safetensors[jax]", "safetensors[numpy]", "safetensors[paddlepaddle]", "safetensors[pinned-tf]", "safetensors[quality]", "safetensors[testing]", "safetensors[torch]"]
dev = ["safetensors[all]"]
jax = ["flax (>=0.6.3)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "safetensors[numpy]"]
mlx = ["mlx (>=0.0.9)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
numpy = ["numpy (>=1.21.6)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
paddlepaddle = ["paddlepaddle (>=2.4.1)", "safetensors[numpy]"]
pinned-tf = ["safetensors[numpy]", "tensorflow (==2.11.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
quality = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "isort (>=5.5.4)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools-rust (>=1.5.2)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
torch = ["safetensors[numpy]", "torch (>=1.10)"]
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 21:00:59 +00:00
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
[[package]]
name = "scikit-learn"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "1.5.2"
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
description = "A set of python modules for machine learning and data mining"
optional = false
python-versions = ">=3.9"
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
]
[package.dependencies]
joblib = ">=1.2.0"
numpy = ">=1.19.5"
scipy = ">=1.6.0"
threadpoolctl = ">=3.1.0"
[package.extras]
benchmark = ["matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "pandas (>=1.1.5)"]
build = ["cython (>=3.0.10)", "meson-python (>=0.16.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "polars (>=0.20.30)", "pooch (>=1.6.0)", "pydata-sphinx-theme (>=0.15.3)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)", "sphinx (>=7.3.7)", "sphinx-copybutton (>=0.5.2)", "sphinx-design (>=0.5.0)", "sphinx-design (>=0.6.0)", "sphinx-gallery (>=0.16.0)", "sphinx-prompt (>=1.4.0)", "sphinx-remove-toctrees (>=1.0.0.post1)", "sphinxcontrib-sass (>=0.3.4)", "sphinxext-opengraph (>=0.9.1)"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
examples = ["matplotlib (>=3.3.4)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "pooch (>=1.6.0)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)"]
install = ["joblib (>=1.2.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)", "threadpoolctl (>=3.1.0)"]
maintenance = ["conda-lock (==2.5.6)"]
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
tests = ["black (>=24.3.0)", "matplotlib (>=3.3.4)", "mypy (>=1.9)", "numpydoc (>=1.2.0)", "pandas (>=1.1.5)", "polars (>=0.20.30)", "pooch (>=1.6.0)", "pyamg (>=4.0.0)", "pyarrow (>=12.0.0)", "pytest (>=7.1.2)", "pytest-cov (>=2.9.0)", "ruff (>=0.2.1)", "scikit-image (>=0.17.2)"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
[[package]]
name = "scipy"
Upgrading all versions. (#1759)
2024-04-18 15:17:40 +00:00
version = "1.13.1"
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
description = "Fundamental algorithms for scientific computing in Python"
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
optional = false
Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
python-versions = ">=3.9"
files = [
Upgrading all versions. (#1759)
2024-04-18 15:17:40 +00:00
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Outlines guided generation (#1539) This WIP PR starts to add grammar support via outlines, currently this PR supports very simple regex grammars and does not optimize for precompiling or caching grammar fsm's. todo: - [X] add simple outlines guidance to `NextTokenChooser` - [X] update protos for grammar - [X] update generation params API - [X] constrain simple grammar - [ ] support parsing more complex grammar into fsm - [ ] support all outline support grammar types - [ ] explore optimizations to avoid recompiling grammars guided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data-raw '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6, "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+" } }' | jq ``` response ```json { "generated_text": "david@example.com" } ``` unguided request ```bash curl -s 'http://localhost:3000/generate' \ --header 'Content-Type: application/json' \ --data '{ "inputs": "make an email for david: \n", "parameters": { "max_new_tokens": 6 } }' | jq ``` response ```json { "generated_text": " email = 'david" } ```
2024-02-15 09:28:10 +00:00
]
[package.dependencies]
numpy = ">=1.22.4,<2.3"
[package.extras]
dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pydevtool", "rich-click", "ruff", "types-psutil", "typing_extensions"]
doc = ["jupyterlite-pyodide-kernel", "jupyterlite-sphinx (>=0.12.0)", "jupytext", "matplotlib (>=3.5)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (>=0.15.2)", "sphinx (>=5.0.0)", "sphinx-design (>=0.4.0)"]
test = ["array-api-strict", "asv", "gmpy2", "hypothesis (>=6.30)", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "sentencepiece"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "0.2.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "SentencePiece python wrapper"
optional = false
python-versions = "*"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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feat(server): add flash attention llama (#144)
2023-04-11 14:38:22 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "setuptools"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "75.2.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Easily download, build, install, upgrade, and uninstall Python packages"
optional = false
New release. (#941) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-29 12:28:22 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "setuptools-75.2.0-py3-none-any.whl", hash = "sha256:a7fcb66f68b4d9e8e66b42f9876150a3371558f98fa32222ffaa5bced76406f8"},
{file = "setuptools-75.2.0.tar.gz", hash = "sha256:753bb6ebf1f465a1912e19ed1d41f403a79173a9acf66a42e7e6aec45c3c16ec"},
fix(ci): fix CVE in github-slug-action (#174)
2023-04-13 10:43:05 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.5.2)"]
core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.collections", "jaraco.functools", "jaraco.text (>=3.7)", "more-itertools", "more-itertools (>=8.8)", "packaging", "packaging (>=24)", "platformdirs (>=2.6.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
cover = ["pytest-cov"]
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
enabler = ["pytest-enabler (>=2.2)"]
test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.11.*)", "pytest-mypy"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "six"
version = "1.16.0"
description = "Python 2 and 3 compatibility utilities"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
files = [
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "sympy"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "1.13.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Computer algebra system (CAS) in Python"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=3.8"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "sympy-1.13.3-py3-none-any.whl", hash = "sha256:54612cf55a62755ee71824ce692986f23c88ffa77207b30c1368eda4a7060f73"},
{file = "sympy-1.13.3.tar.gz", hash = "sha256:b27fd2c6530e0ab39e275fc9b683895367e51d5da91baa8d3d64db2565fec4d9"},
Init
2022-10-08 10:30:12 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
mpmath = ">=1.1.0,<1.4"
[package.extras]
dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
Upgrade to 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-07-17 05:08:52 +00:00
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
[[package]]
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
name = "texttable"
version = "1.7.0"
description = "module to create simple ASCII tables"
optional = true
python-versions = "*"
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
files = [
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
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Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "tokenizers"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "0.20.1"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
description = ""
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
optional = false
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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feat(server): add flash attention llama (#144)
2023-04-11 14:38:22 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
[package.dependencies]
Update to SynapseAI 1.16.0 (#167) Co-authored-by: Alexey Fadeev <alexey.fadeev@intel.com>
2024-07-03 09:08:56 +00:00
huggingface-hub = ">=0.16.4,<1.0"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
dev = ["tokenizers[testing]"]
Update to SynapseAI 1.16.0 (#167) Co-authored-by: Alexey Fadeev <alexey.fadeev@intel.com>
2024-07-03 09:08:56 +00:00
docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "tomli"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "2.0.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "A lil' TOML parser"
optional = false
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"},
{file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"},
fix(ci): fix CVE in github-slug-action (#174)
2023-04-13 10:43:05 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "tqdm"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "4.66.5"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Fast, Extensible Progress Meter"
optional = false
python-versions = ">=3.7"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
{file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
fix(server): fix hf_transfer issue with private repos (#203)
2023-04-19 15:36:16 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
colorama = {version = "*", markers = "platform_system == \"Windows\""}
[package.extras]
Adding Idefics multi modal model. (#842) Co-Authored-By: Victor Sanh <victorsanh@gmail.com> # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 12:38:49 +00:00
dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
notebook = ["ipywidgets (>=6)"]
slack = ["slack-sdk"]
telegram = ["requests"]
[[package]]
name = "transformers"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "4.45.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
optional = false
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
python-versions = ">=3.8.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
{file = "transformers-4.45.2-py3-none-any.whl", hash = "sha256:c551b33660cfc815bae1f9f097ecfd1e65be623f13c6ee0dda372bd881460210"},
{file = "transformers-4.45.2.tar.gz", hash = "sha256:72bc390f6b203892561f05f86bbfaa0e234aab8e927a83e62b9d92ea7e3ae101"},
feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438) Let's start discussing implementation. - Need to expose the quantization scripts (either included here or add doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa) - Make sure GPTQ works for multiple models (priority to Falcon). Currently it means that every place we use `get_{tensor|sharded}` to check for quantization. My idea is to reintegrate as much as possible into `utils/layer.py` by expanding `load_multi` to be a bit more generic. This might require some thinking, but ultimately the `qweight,qzeros,scales,g_idx` should be in a single place, and independant of bias presence. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 10:27:01 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
filelock = "*"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
huggingface-hub = ">=0.23.2,<1.0"
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 15:18:54 +00:00
numpy = ">=1.17"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
packaging = ">=20.0"
pyyaml = ">=5.1"
regex = "!=2019.12.17"
requests = "*"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
safetensors = ">=0.4.1"
sentencepiece = {version = ">=0.1.91,<0.1.92 || >0.1.92", optional = true, markers = "extra == \"sentencepiece\""}
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
tokenizers = ">=0.20,<0.21"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
tqdm = ">=4.27"
[package.extras]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
accelerate = ["accelerate (>=0.26.0)"]
agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
benchmark = ["optimum-benchmark (>=0.3.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
codecarbon = ["codecarbon (==1.2.0)"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
deepspeed = ["accelerate (>=0.26.0)", "deepspeed (>=0.9.3)"]
deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.26.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.20,<0.21)", "urllib3 (<2.0.0)"]
dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "libcst", "librosa", "nltk (<=3.8.1)", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
Upgrade SynapseAI version to 1.17.0 (#208) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
2024-08-26 08:49:29 +00:00
flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
ftfy = ["ftfy"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
integrations = ["optuna", "ray[tune] (>=2.7.0)", "sigopt"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
modelcreation = ["cookiecutter (==1.7.3)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
natten = ["natten (>=0.14.6,<0.15.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
optuna = ["optuna"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "libcst", "rich", "ruff (==0.5.1)", "urllib3 (<2.0.0)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
ray = ["ray[tune] (>=2.7.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
ruff = ["ruff (==0.5.1)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
sagemaker = ["sagemaker (>=2.31.0)"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
Update peft + transformers + accelerate + bnb + safetensors (#1646)
2024-03-15 12:23:26 +00:00
serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
sigopt = ["sigopt"]
sklearn = ["scikit-learn"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
Add support for Llama 3 rotary embeddings (#2286) * Add support for Llama 3 rotary embeddings * Update transformers to 4.43
2024-07-23 15:18:54 +00:00
tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
tiktoken = ["blobfile", "tiktoken"]
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
timm = ["timm (<=0.9.16)"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
tokenizers = ["tokenizers (>=0.20,<0.21)"]
torch = ["accelerate (>=0.26.0)", "torch"]
Upgrade transformers (fix protobuf==3.20 issue) (#795) # What does this PR do? Fixes #531 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-11 14:46:08 +00:00
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.20,<0.21)", "torch", "tqdm (>=4.27)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
video = ["av (==9.2.0)", "decord (==0.6.0)"]
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
vision = ["Pillow (>=10.0.1,<=15.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
[[package]]
name = "triton"
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 11:34:44 +00:00
version = "3.0.0"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
description = "A language and compiler for custom Deep Learning operations"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = "*"
files = [
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 11:34:44 +00:00
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Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
]
[package.dependencies]
filelock = "*"
[package.extras]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
build = ["cmake (>=3.20)", "lit"]
Some small fixes for the Torch 2.4.0 update (#2304) * Fix GPTQ autotune data type to be compatible with Torch 2.4.0 * Update poetry lock file * Fix small PaliGemma logprob differences after the torch update
2024-07-25 11:34:44 +00:00
tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
tutorials = ["matplotlib", "pandas", "tabulate"]
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "typer"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
version = "0.6.1"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
optional = false
python-versions = ">=3.6"
files = [
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
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Init
2022-10-08 10:30:12 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
click = ">=7.1.1,<9.0.0"
[package.extras]
all = ["colorama (>=0.4.3,<0.5.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2.17.0,<3.0.0)"]
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)"]
test = ["black (>=22.3.0,<23.0.0)", "coverage (>=5.2,<6.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.910)", "pytest (>=4.4.0,<5.4.0)", "pytest-cov (>=2.10.0,<3.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<2.0.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "typing-extensions"
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
version = "4.12.2"
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 13:31:27 +00:00
description = "Backported and Experimental Type Hints for Python 3.8+"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
optional = false
Add AWQ quantization inference support (#1019) (#1054) # Add AWQ quantization inference support Fixes https://github.com/huggingface/text-generation-inference/issues/781 This PR (partially) adds support for AWQ quantization for inference. More information on AWQ [here](https://arxiv.org/abs/2306.00978). In general, AWQ is faster and more accurate than GPTQ, which is currently supported by TGI. This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors (in `requirements.txt`, just one line change). Quick way to test this PR would be bring up TGI as follows: ``` text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq text-generation-launcher \ --huggingface-hub-cache ~/.cache/huggingface/hub/ \ --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \ --trust-remote-code --port 8080 \ --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \ --quantize awq ``` Please note: * This PR was tested with FlashAttention v2 and vLLM. * This PR adds support for AWQ inference, not quantizing the models. That needs to be done outside of TGI, instructions [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa). * This PR only adds support for `FlashLlama` models for now. * Multi-GPU setup has not been tested. * No integration tests have been added so far, will add later if maintainers are interested in this change. * This PR can be tested on any of the models released [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models). Please refer to the linked issue for benchmarks for [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq) vs [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ). Please note, AWQ has released faster (and in case of Llama, fused) kernels for 4-bit GEMM, currently at the top of the `main` branch at https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit that has been tested to work. We can switch to latest commit later on. ## Who can review? @OlivierDehaene OR @Narsil --------- # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com> Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 13:31:27 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Softcapping for gemma2. (#2273) * Softcapping for gemma2. * Less clutter. * No access to transformers config, only config_dict here. * 0.0 is the null value in the C++ API.
2024-07-22 16:27:10 +00:00
{file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
Init
2022-10-08 10:30:12 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "tzdata"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2024.2"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Provider of IANA time zone data"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
python-versions = ">=2"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
{file = "tzdata-2024.2-py2.py3-none-any.whl", hash = "sha256:a48093786cdcde33cad18c2555e8532f34422074448fbc874186f0abd79565cd"},
{file = "tzdata-2024.2.tar.gz", hash = "sha256:7d85cc416e9382e69095b7bdf4afd9e3880418a2413feec7069d533d6b4e31cc"},
fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "urllib3"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "2.2.3"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "HTTP library with thread-safe connection pooling, file post, and more."
optional = false
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3.8"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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feat(launcher): Log server stdout (#19) Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-01-05 11:01:23 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
feat: relax mistral requirements (#1351) Close #1253 Close #1279
2023-12-15 11:52:24 +00:00
h2 = ["h2 (>=4,<5)"]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"]
[[package]]
name = "win32-setctime"
version = "1.1.0"
description = "A small Python utility to set file creation time on Windows"
optional = false
python-versions = ">=3.5"
files = [
feat(launcher): Log server stdout (#19) Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-01-05 11:01:23 +00:00
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feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.extras]
dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
[[package]]
name = "wrapt"
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
version = "1.16.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Module for decorators, wrappers and monkey patching."
optional = false
chore: update to torch 2.1.0 (#1182) Close #1142
2023-11-23 12:38:50 +00:00
python-versions = ">=3.6"
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feat: add distributed tracing (#62)
2023-02-13 12:02:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "xxhash"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "3.5.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Python binding for xxHash"
Aligin the source code with main branch 2.0.4 Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-09-24 03:06:55 +00:00
optional = true
This should prevent the PyTorch overriding. (#767) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 19:54:39 +00:00
python-versions = ">=3.7"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[[package]]
name = "yarl"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
version = "1.16.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
description = "Yet another URL library"
Update dependencies (#69)
2024-02-25 12:07:47 +00:00
optional = false
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
python-versions = ">=3.9"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
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Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
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fix(server): fix missing datasets in quantize
2023-07-27 12:50:45 +00:00
]
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[package.dependencies]
idna = ">=2.0"
multidict = ">=4.0"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
propcache = ">=0.2.0"
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
[[package]]
name = "zipp"
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
version = "3.20.2"
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
description = "Backport of pathlib-compatible object wrapper for zip files"
optional = false
python-versions = ">=3.8"
files = [
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
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{file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
]
[package.extras]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
cover = ["pytest-cov"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
Mllama flash version (#2585) * Working loading state. * Preprocessing. * Working state ? (Broke idefics1 temporarily). * Cleaner condition. * Fix idefics. * Updating config, removing TODO * Mllama * Ugrade transformers 4.45 * Flashing mllama. * Starting to get there. * Working state. * Integrations tests for mllama (cutting to 10 tokens because there seems' to be instability after (meaning size of the batch matters. * Updating model link. * Earlier assert. * Fix vlm ? * remove log. * Force ignore all images but last. * Default dtype bfloat16. * Update integration test after switch to bf16. * Remove dead code. * Removed dead code. * Upgrade the flake to latest transformers/tokenizers * Move to hf tgi-nix * Upgrade to 0.5.0
2024-10-02 09:22:13 +00:00
enabler = ["pytest-enabler (>=2.2)"]
test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
type = ["pytest-mypy"]
Making `make install` work better by default. (#2004) # What does this PR do? Making `make install` a much better sane default to start local dev environments. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-06-04 17:38:46 +00:00
feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-03 15:22:45 +00:00
[metadata]
lock-version = "2.0"
Merge BNB 4bit. (#770) # What does this PR do? See #626 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> --------- Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 21:00:59 +00:00
python-versions = ">=3.9,<3.13"
Upgrade to SynapseAI 1.18 (#227) Signed-off-by: yuanwu <yuan.wu@intel.com> Co-authored-by: Thanaji Rao Thakkalapelli <tthakkalapelli@habana.ai>
2024-10-31 19:14:44 +00:00
content-hash = "d169e52a2daaf41488cf7191e3f4ff209d39125941a6d0e656001aae534b1e8d"
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