Commit Graph

434 Commits

Author SHA1 Message Date
BaihuiJin
15e5df1cc4
BS round up to BUCKET_SIZE to prevent capture graph when graph input not change (#185) 2024-07-16 09:42:46 +02:00
BaihuiJin
aac547dd82
Clear previous hpu_graphs when graph shape changed to save memory (#176) 2024-07-11 15:19:17 +02:00
Jacek Czaja
5df20f88ff
Fix to non-LLAMA models (#177)
Co-authored-by: Jacek Czaja <jczaja@habana.ai>
2024-07-04 13:42:24 +02:00
Jacek Czaja
c64b5b75e2
[TORCH COMPILE] Ignore HPU GRAPHS env var when eager mode is used (#165)
Co-authored-by: Jacek Czaja <jczaja@habana.ai>
2024-07-03 15:17:27 +02:00
Karol Damaszke
4b4382c6f8
Fix dtype mismatch in HeterogeneousFrequencyPenaltyLogitsProcessor (#163) 2024-07-03 10:57:41 +02:00
Vidya Galli
ca1b2f4994
Updated kv cache for starcoder (#128) 2024-06-14 22:36:44 +02:00
Jacek Czaja
ef86232c94
[Torch.compile] Enable llama-2-7b (#157)
Co-authored-by: Jacek Czaja <jczaja@habana.ai>
2024-06-14 15:56:23 +02:00
Martin Iglesias Goyanes
8c847f2b60 Fixing frequency penalty (#1811)
Thank you so much for the work you are doing, this is my little
contribution to this great thing you have built. I hope it is useful and
helpful, please don't hesitate to discuss any matters that are not
clear!

I am basing my implementation of frequency penalty on OpenAI's
implementation:
https://platform.openai.com/docs/guides/text-generation/parameter-details

The problem I see with TGI's current implementation is that is not
taking into account the frequency of tokens which have already been
sampled in the current generation stream. Also, the scaling is of the
adjusted token logits is done differently for positive and negative
logits. While in OpenAI's implementation token frequency is taking into
account and the scaling is always done with a subtraction (if penalty is
positive) or add operation (if penalty is negative).

This leads to corrupt generations as I mentioned in issue #1810 .
Moreover, after my tests, other issues are also gone like the one about
some request's with ``penalty_frequency = 1.0`` overruling other
requests (with ``frequency_penalty = 0.0``) in the same batch and
therefore corrupting all generations in the batch. Basically, padding
does not affect this implementation so I believe this ``score *=
input_ids.ne(0)`` is not needed anymore.



Frequency penalty | -1.0 | 0.0 | 1.0
-- | -- | -- | --
Before my change | https://paste.mozilla.org/JxqGJkWY |
https://paste.mozilla.org/hrztJ56h | https://paste.mozilla.org/pBSEH2zw
After my change | https://paste.mozilla.org/7gXCi7zo |
https://paste.mozilla.org/ZR9rJ92g | https://paste.mozilla.org/gHaD2YnC

---------

Co-authored-by: martini <martin.iglesiasgoyanes@adyen.com>
2024-06-10 14:05:08 +03:00
OlivierDehaene
91352b1b71 fix: use get_speculate to the number of layers (#1737) 2024-06-10 14:02:23 +03:00
Nicolas Patry
6ca39843b4 Small CI cleanup. (#1801)
# What does this PR do?

Just unifying some branches and making intentions clearer (no cuda graph
when 0 all the way in the launcher)

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2024-06-10 14:01:01 +03:00
Nicolas Patry
3f3a1a6a66 Better graceful shutdown. (#1827)
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2024-06-10 14:00:26 +03:00
Nicolas Patry
7641cda775 Dummy CI run. (#1817)
# What does this PR do?

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2024-06-10 13:57:59 +03:00
Nicolas Patry
a788888619 Fixing qwen2. (#1818)
# What does this PR do?

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2024-06-10 13:57:52 +03:00
Nicolas Patry
388af49916 Blunder (#1815)
# What does this PR do?

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2024-06-10 13:57:47 +03:00
Wang, Yi
62a83fd800 add intel xpu support for TGI (#1475)
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---------

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-06-10 13:16:45 +03:00
Nicolas Patry
2ed6242816 Use the generation config. (#1808)
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2024-06-10 09:53:00 +03:00
drbh
ab59a5e346 feat: improve temperature logic in chat (#1749)
This PR adds support for `do_sample` to chat to enable greedy sampling

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-06-10 09:50:25 +03:00
drbh
ec85883703 fix: avoid frequency and repetition penalty on padding tokens (#1765)
This PR resolves an issue with the penalty processors during batched
generation where extra padding tokens incorrectly impact the penalty
scores.

generation is impacted in the case where at least one item in the batch
includes a `frequency_penalty`

reproduction script below
```python
import requests
from concurrent import futures
import time

headers = {
    "Content-Type": "application/json",
}

json_data = {
    "inputs": "[INST] Whats the capitol of France? [/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 20,
        "do_sample": False,
    },
}


json_data2 = {
    "inputs": "<s>[INST]Write a mind bending story: I saw a puppy a cat a rat and a raccoon during my bike ride in the park[/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 2,
        "do_sample": False,
        # OFFENDING LINE
        "frequency_penalty": 1.05,
    },
}

base_url = "http://localhost:3000/generate"


def req():
    response = requests.post(base_url, headers=headers, json=json_data)
    print("[req ]", response.json())


def req2():
    response = requests.post(base_url, headers=headers, json=json_data2)
    print("[req2]", response.json())


n = 1

for i in range(0, 3):
    print(f"- {n} threads -")
    with futures.ThreadPoolExecutor(max_workers=n) as executor:
        executor.submit(req)
        for i in range(3):
            executor.submit(req2)

    n += 1

# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': ' As""%\n================'}
# [req2] {'generated_text': ' As""%%$\n================'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

# output with this PR's changes:
# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

```

**divergence from expected generation is easier to reproduce with
batched grammar requests as they are more sensitive to unexpected
outputs.

this PR resolves the issue by setting the penalty score to 0 where input
ids are padding tokens (0).

---------

Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-06-10 09:29:20 +03:00
Nicolas Patry
57b31f410d Idefics2. (#1756)
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2024-06-10 09:29:08 +03:00
Nicolas Patry
4f8ca6049e Phi3 support (#1797)
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2024-06-10 09:27:01 +03:00
fxmarty
5b162c7026 Make --cuda-graphs work as expected (bis) (#1768)
This was ignored up to now, even with `--cuda-graphs 0`.

With this fix, `--cuda-graphs` is obeyed to.
2024-06-10 09:24:43 +03:00
Nicolas Patry
11c16aa64c Upgrading all versions. (#1759) 2024-06-03 15:39:47 +03:00
Karol Damaszke
0e8f8726db
Warmup all decode buckets (#152)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-29 22:46:55 +02:00
Karol Damaszke
7b879fd1d8
Pad next token chooser parameters with empty logits processors (#151)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-29 22:43:56 +02:00
Jimin Ha
1023de8048
Add flash_attention argument options for Mistral (#145)
Co-authored-by: Karol Damaszke <karol.damaszke@intel.com>
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-27 20:00:42 +02:00
Karol Damaszke
32acdd55b4
Add grammar support (#140)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-20 11:16:34 +02:00
Sylwester Fraczek
fe16a465a0
causal_lm server tests rebased (#139)
Co-authored-by: Sylwester Fraczek <sfraczek@habana.ai>
Co-authored-by: Jacek Czaja <jczaja@habana.ai>
2024-05-06 15:55:35 +02:00
Karol Damaszke
bad7fe720a
Fix warmup shapes for corner cases (#136)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-05-06 11:35:27 +02:00
Karol Damaszke
600d033c04 Merge branch 'habana-main' into rebase_tgi_2.0 2024-04-29 09:44:45 +03:00
regisss
37aabf8571
Move call to adapt_transformers_to_gaudi earlier in the code (#133) 2024-04-26 11:07:27 +02:00
OlivierDehaene
c6a31b9e2b v2.0.0 (#1736) 2024-04-26 07:42:52 +00:00
OlivierDehaene
f6d5c2edf2 feat: medusa v2 (#1734) 2024-04-26 07:42:37 +00:00
Nicolas Patry
935d56abfe Fp8 Support (#1726)
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---------

Co-authored-by: Dong Shin <d0104.shin@gmail.com>
2024-04-25 17:58:11 +03:00
OlivierDehaene
d1d0b3cbd6 hotfix: mixtral 2024-04-25 17:51:46 +03:00
OlivierDehaene
a1b65e5919 fix: fix CohereForAI/c4ai-command-r-plus (#1707)
@Narsil @drbh this will update flash attention v2 and vllm.
You will need to re-install them.
2024-04-25 17:51:35 +03:00
Nicolas Patry
2b2f4dee94 Adding Llava-Next (Llava 1.6) with full support. (#1709)
- Changed all models to extract `embed_tokens` in order to enable llava
to separately call the embeddings and the core model layers.
- Added VlmCausalLM to inherit from FlashMistral in order to be
maximally supported. The only added logics sits on top and parses images
into pixel values, preallocates input_ids space for the image
embeddings, and passes them for the model.
- Added Clip for the vision tower.
- Didn't add flash for the vision tower since there's no padding anyway.
- Added heuristic (potentially incomplete) to calculate number of
features *before* calculating the clip patches (allows for easier logic
reuse of the LLM under the hood).

Still needs to be done:

- [x] Implement the image parsing in the controller side, to avoid
downloading n times per TP shard and also refusing requests too large
early and avoid issues where the truncation actually truncates the
image.
- [ ] Make sure it works with quantization properly.
- [x] Make sure it works with TP>1

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2024-04-25 14:30:55 +00:00
Nicolas Patry
3417398c9a Force weights_only (before fully breaking pickle files anyway). (#1710)
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2024-04-25 15:10:53 +03:00
Nicolas Patry
fec3f8f21c Fixing cohere tokenizer. (#1697) 2024-04-25 15:10:46 +03:00
Nicolas Patry
fe063b8118 Pickle conversion now requires --trust-remote-code. (#1704)
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2024-04-25 15:09:00 +03:00
Nicolas Patry
29c316e5bb Add cuda graphs sizes and make it default. (#1703)
# What does this PR do?

```
text-generation-launcher --model-id XXX # Uses cuda graphs by default
text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
```
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2024-04-25 15:08:54 +03:00
OlivierDehaene
dc1ab2001d feat: Add dbrx support (#1685)
Close #1679
2024-04-25 14:07:28 +03:00
drbh
56670398f3 fix: handle batches with and without grammars (#1676)
This PR correctly handles batches with a mixture of constrained and non
constrained generations.

Currently if batch contains mixed generations the generation will throw
an error because it will incorrectly attempt to constrain a request with
an empty grammar.

We now handled `None` grammars and only apply the mask if needed

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1643
2024-04-25 14:06:48 +03:00
OlivierDehaene
da4199ed97 feat: cohere (#1660) 2024-04-25 12:39:14 +03:00
SeongBeomLEE
097e72a672 fix: LlamaTokenizerFast to AutoTokenizer at flash_mistral.py (#1637)
# What does this PR do?

A few cases where you're using a mistral structure or mixtral structure
but not a llama tokenizer, why not make it to call the AutoTokenizer in
exception handling.

Similar PR #619

@Narsil
2024-04-25 12:35:44 +03:00
Nicolas Patry
6729783a19 Remove unecessary cuda graph. (#1664)
# What does this PR do?

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2024-04-25 12:35:24 +03:00
drbh
ab074c81b7 fix: improve tool type, bump pydantic and outlines (#1650)
This PR resolves a couple

- [X] adjusts the tool response to align with openai's tools response
type
- [X] bumps pydantic to `2.6.4` in all apps (resolves dependency issue
when running tests)
- [X] bump `outlines` version and fix import for new name
2024-04-25 12:34:55 +03:00
drbh
d888bc2828 feat: support force downcast after FastRMSNorm multiply for Gemma (#1658)
This PR adds `force_downcast_after` to `FastRMSNorm.forward` which is
used in the Gemma model. References
https://github.com/huggingface/transformers/pull/29402 and
https://github.com/huggingface/transformers/pull/29729

Setting `force_downcast_after=True` will perform the `hidden_states *
weight` multiplication in f32 and then downcast to half. This differs
slightly from the current implementation which first casts the
`hidden_states` to a half and then multiples.
2024-04-25 12:32:42 +03:00
drbh
d4aebbd10a fix: correctly index into mask when applying grammar (#1618)
This PR fixes how the grammar mask is index when generating text and
adds a new test to ensure the grammars work with non flash models
2024-04-25 10:16:16 +03:00
Nicolas Patry
0390b28b85 Fix idefics default. (#1614)
# What does this PR do?

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2024-04-25 10:12:13 +03:00
drbh
e259625b8b fix: Handle concurrent grammar requests (#1610)
This PR fixes parallel grammar requests, currently grammar states are
not concatenated correctly when a new request is added to the batch and
this results in incorrect generation. This PR updates the `concatenate`
function to correctly include the previous states.

fixes: #1601
2024-04-25 10:11:40 +03:00
OlivierDehaene
666cdaaf16 feat: Qwen2 (#1608)
See #1584

---------

Co-authored-by: Cheng Kuan Yong Jason <jasoncky96@gmail.com>
2024-04-25 09:21:22 +03:00
OlivierDehaene
7c6a47bb7a feat: starcoder2 (#1605) 2024-04-25 09:18:55 +03:00
Nicolas Patry
21d52c9ca1 Revamp medusa implementation so that every model can benefit. (#1588)
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2024-04-25 09:13:03 +03:00
OlivierDehaene
a461257066 feat: add support for Gemma (#1583) 2024-04-24 18:08:23 +03:00
OlivierDehaene
3c6e6d8c3f fix(router): fix openapi and add jsonschema validation (#1578) 2024-04-24 18:07:44 +03:00
Nicolas Patry
5a54d915ae Fix mistral with length > window_size for long prefills (rotary doesn't create long enough cos, sin). (#1571)
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2024-04-24 18:05:34 +03:00
OlivierDehaene
2ac1b55c95 v1.4.1 (#1568) 2024-04-24 15:42:59 +03:00
OlivierDehaene
31b5e37f49 chore: add pre-commit (#1569) 2024-04-24 15:32:02 +03:00
drbh
55acb86f42 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"
}
```
2024-04-24 14:57:37 +03:00
Nicolas Patry
686b56a0c0 Small cleanup. (#1560)
Using a single `os.getenv` statement instead of multiple.
Should make truthful values easier to catch

In the end didn't move towards full CLI because modifying globals in
Python is error prone (depends on code import order).

Added an error when mamba is launched with TP.


# What does this PR do?

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2024-04-24 14:42:35 +03:00
Nicolas Patry
e93cc34a22 Improving mamba runtime by using updates (#1552)
- Move float16 to bfloat16, which has less imprecisions (load test are
  failing with the update kernels + f16, all working under bf16).

  Another note, is that we are not respecting the layer norm in f32
  defined in the configuration (this is OK in my book, but that could
  impact the f16 precision)

- Moved to update kernels. Triton overhead is super high, removed by
  switching to cuda graphs works great (update cuda graph is available
  in TRT-LLM if needed, seems *exactly* like the regular ssm kernel.

- Moved inference_params struct in order to make only 2 tensors, to
  reduce the overhead of copying back and forth to the cuda graphs.

- Left over overhead seems entirely in the tokenization bit. (Still 4
  copies are paid before launching the graph)


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2024-04-24 13:21:39 +03:00
OlivierDehaene
0c207f71ed feat: experimental support for cuda graphs (#1428)
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-24 13:15:45 +03:00
Ilyas Moutawwakil
777e519277 ROCm AWQ support (#1514)
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This PR adds the possibility to run AWQ models with Exllama/GPTQ
kernels, specifically for ROCm devices that support Exllama kernels but
not AWQ's GEMM.

This is done by :
- un-packing, reordering and re-packing AWQ weights when `--quantize
gptq` but the model's `quant_method=awq`.
- avoiding overflows when adding 1 to zeros in exllama and triton.

Ref: https://github.com/casper-hansen/AutoAWQ/pull/313

## Before submitting
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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-24 09:21:34 +00:00
OlivierDehaene
f1d8da3ba6 feat(server): add frequency penalty (#1541) 2024-04-24 08:43:50 +00:00
drbh
51a4e62ed4 Impl simple mamba model (#1480)
This draft PR is a work in progress implementation of the mamba model.
This PR currently loads weights, and produces correct logits after a
single pass.

This PR still needs to correctly integrate this model so it produces
tokens as expected, and apply optimization to avoid all copies during
runtime/unnecessary operations.

[Mamba: Linear-Time Sequence Modeling with Selective State Spaces
(Albert Gu and Tri Dao)](https://arxiv.org/abs/2312.00752)
https://github.com/johnma2006/mamba-minimal

https://github.com/huggingface/candle/blob/main/candle-examples/examples/mamba-minimal/model.rs
https://github.com/huggingface/transformers/pull/28094

Notes: this dev work is currently targeting `state-spaces/mamba-130m`,
so if you want to test please use that model. Additionally when starting
the router the prefill needs to be limited: `cargo run --
--max-batch-prefill-tokens 768 --max-input-length 768`

Integration tests have been added and basic functionality such as model
loading is supported.

```bash
cd integration-tests
pytest -vv models/test_fused_kernel_mamba.py
```
- [x] add tests
- [x] load model
- [x] make simple request
- [ ] resolve warmup issue
- [ ] resolve output issues

fetching models tested during dev
```bash
text-generation-server download-weights state-spaces/mamba-130m
text-generation-server download-weights state-spaces/mamba-1.4b
text-generation-server download-weights state-spaces/mamba-2.8b
```

The server can be run
```bash
cd server
 MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 python text_generation_server/cli.py serve state-spaces/mamba-2.8b
```

router
```bash
cargo run
```

make a request
```bash
curl -s localhost:3000/generate \
    -X POST \
    -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
    -H 'Content-Type: application/json' | jq
```

response
```json
{
  "generated_text": "\n\nDeep learning is a machine learning technique that uses a deep neural network to learn from data."
}
```

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-23 11:45:11 +03:00
Dean Wyatte
27daa511ec GPTNeoX: Use static rotary embedding (#1498)
# What does this PR do?

`transformers` 4.35 removed rotary embeddings from GPTNeoX's weights
([link to line
diff](253f9a3f97 (diff-0e2a05d86c82e96f516db8c14070ceb36f53ca44c6bc21a9cd92ad2e777b9cf1R298))).
This applies the same fix as
https://github.com/huggingface/text-generation-inference/pull/793 which
generates them on-the-fly using the appropriate value from the config
file

Fixes
https://github.com/huggingface/text-generation-inference/issues/1460

## Before submitting
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other checks if that's the case).
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2024-04-23 09:21:21 +03:00
Nicolas Patry
433934519c Fixing top_n_tokens. (#1497)
Superseeds #1459

The fix works as follows.
We updated next_token_chooser to return all logprbs, then
batch_top_n_tokens, now also gets accepted_ids + speculated_length (so
it knows how to interpret the flat logprobs).

We then update the code to return lists ot `Tokens` that it expects.
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2024-04-23 08:49:24 +03:00
OlivierDehaene
efd4b97d15 v1.4.0 (#1494) 2024-04-22 15:47:42 +03:00
fxmarty
4b376b30f1 GPTQ support on ROCm (#1489)
Tested with
```
CUDA_VISIBLE_DEVICES=0 text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
EXLLAMA_VERSION=1 CUDA_VISIBLE_DEVICES=0 text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
CUDA_VISIBLE_DEVICES="0,1" text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
```

all with good and identical results on MI210.

---------

Co-authored-by: Felix Marty <felix@hf.co>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
2024-04-22 15:38:50 +03:00
Nicolas Patry
b064b33e8b Add sealion mpt support (#1477)
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---------

Co-authored-by: Choon Meng Tan <choonmeng@aisingapore.org>
Co-authored-by: David Ong Tat-Wee <13075447+ongtw@users.noreply.github.com>
2024-04-22 15:37:05 +03:00
Nicolas Patry
ea2aa53805 Reinstate exl2 with tp (#1490)
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2024-04-22 15:36:57 +03:00
drbh
b2fc097b2b feat: adds phi model (#1442)
This PR adds basic modeling for phi-2

run
```bash
text-generation-server \
    serve \
    microsoft/phi-2 \
    --revision 834565c23f9b28b96ccbeabe614dd906b6db551a
```

test
```bash
curl -s localhost:3000/generate \
   -X POST \
   -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
   -H 'Content-Type: application/json' | jq .
```

notes
- recently (~1 day ago) the Phi weights and model were updated to
accommodate adding [GQA/MQA attention to the
model.](https://github.com/huggingface/transformers/pull/28163) This
impl expects the original model format so a fixed revision is required
at the moment.
- this PR only includes a basic implementation of the model and can
later be extended for support Flash and Sharded versions as well as make
use of better optimization
2024-04-22 13:06:38 +03:00
Nicolas Patry
2a3a9c526b Fixing non divisible embeddings. (#1476)
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2024-04-22 12:48:59 +03:00
PYNing
e930ad9cec Fix local load for Medusa (#1420)
# What does this PR do?

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Close #1418 
Close #1415

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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      to it if that's the case.
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2024-04-22 09:30:41 +03:00
R. P. Ruiz
92ddb41d95 Fix missing make target platform for local install: 'install-flash-attention-v2' (#1414) 2024-04-22 09:18:00 +03:00
OlivierDehaene
118344b99d fix: fix local loading for .bin models (#1419) 2024-04-22 09:17:52 +03:00
OlivierDehaene
62646c2a54 v1.3.4 2024-04-22 09:08:34 +03:00
Nicolas Patry
8cc4306f72 Fix local load for peft (#1373)
local directory overloaded still needs the directory to locate the
weights files correctly.

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2024-04-22 09:03:34 +03:00
OlivierDehaene
7eeabb9cda feat: update exllamav2 kernels (#1370)
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-22 09:02:53 +03:00
Nicolas Patry
be05972911 Peft safetensors. (#1364)
Works by removing adapter_model.safetensors from being detected as the
core model file (which skips the real peft detection).

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2024-04-22 09:02:31 +03:00
OlivierDehaene
b7299e1b7f fix: fix gpt-q with groupsize = -1 (#1358) 2024-04-19 15:05:50 +03:00
OlivierDehaene
5ff9e81952 fix: fix offline (#1341) (#1347)
@oOraph

---------

Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>
2024-04-19 14:56:25 +03:00
OlivierDehaene
ecb0db45af fix: fix logic if sliding window key is not present in config (#1352) 2024-04-19 14:56:10 +03:00
OlivierDehaene
a95e6d603d feat: relax mistral requirements (#1351)
Close #1253
Close #1279
2024-04-19 14:50:24 +03:00
OlivierDehaene
bb6200503c fix: max_past default value must be -1, not 0 (#1348) 2024-04-19 14:18:05 +03:00
OlivierDehaene
214ec0eb49 fix: only keep stop sequence buffer if we have some 2024-04-19 14:18:00 +03:00
OlivierDehaene
04dbf7a506 fix: slice stopping criteria buffer 2024-04-19 14:17:52 +03:00
OlivierDehaene
b3c2d7291e fix: fix quant linear autotune 2024-04-19 14:17:39 +03:00
OlivierDehaene
28fcdcca6d fix: fix triton OutOfResources import 2024-04-19 14:17:32 +03:00
OlivierDehaene
5c9ef069ed feat: add more latency metrics in forward (#1346) 2024-04-19 13:41:34 +03:00
OlivierDehaene
c974437ba7 fix: fix gpt-q params loading 2024-04-19 12:12:50 +03:00
OlivierDehaene
f9b58ac7a1 feat: add quant to mixtral (#1337) 2024-04-18 16:32:50 +03:00
OlivierDehaene
09c556dbd7 v1.3.1 2024-04-18 16:32:07 +03:00
OlivierDehaene
79f268f95a chore: formatting 2024-04-18 16:26:00 +03:00
OlivierDehaene
9aef902982 feat: mixtral (#1328) 2024-04-18 12:39:52 +00:00
Nicolas Patry
a7f52f3812 Speculative (#1308) 2024-04-18 12:39:39 +00:00
Karol Damaszke
30cc78773e
Skip server tests of not enabled models (#125)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-04-09 14:15:41 +02:00
Karol Damaszke
d957e32601
Add Habana copyright header (#122)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-04-08 18:06:21 +02:00
Karol Damaszke
b0de25a285
Don't set rope_scaling for unsupported models (#115)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-04-02 12:12:02 +02:00
Karol Damaszke
7342baa2eb
Add support for rope_scaling and remove is_optimized_for_gaudi (#112)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-03-29 15:07:32 +01:00
Karol Damaszke
bf5263b88b
Disable watermark with FP8 quantization (#114)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-03-27 13:32:20 +01:00
jkaniecki
56f00a552b
Adjust warmup to all possible bucket sizes and decode batch size = 1 (#113) 2024-03-27 11:59:51 +01:00
Karol Damaszke
b45f648483
Add warmup for logits processors (#107)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-03-18 15:17:47 +01:00
yuanwu2017
a4d5c3f40f
Fix the generate_stream crash in concurrent query (#105)
Signed-off-by: yuanwu <yuan.wu@intel.com>
2024-03-15 10:54:56 +01:00
Yao Matrix
7149ac30e6
Fix the issue of out of range (#98)
Signed-off-by: yuanwu <yuan.wu@intel.com>
Co-authored-by: yuanwu <yuan.wu@intel.com>
2024-03-13 10:09:53 +01:00
Karol Damaszke
80ae9ead28
Set MAX_TOTAL_TOKENS automatically (#91)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-03-01 11:25:15 +01:00
Karol Damaszke
a5c788cfe4
Remove redundant fill op (#83) (#90)
Co-authored-by: mswiniarsk <156412439+mswiniarsk@users.noreply.github.com>
2024-03-01 01:32:02 +01:00
Karol Damaszke
03c2123244
Use batched index_copy (#73) (#89)
Co-authored-by: madamczykhabana <110973826+madamczykhabana@users.noreply.github.com>
2024-02-29 15:45:16 +01:00
Karol Damaszke
7dbf4bf7a4
Improve tensor slicing performance (#66) (#87)
Co-authored-by: mswiniarsk <156412439+mswiniarsk@users.noreply.github.com>
2024-02-29 10:48:54 +01:00
Karol Damaszke
3831f1bed5
Add warmup for shift operation (#59) (#86) 2024-02-29 09:19:28 +01:00
Karol Damaszke
022ce1eaaf
Overhead reduction (#58) (#85)
Co-authored-by: mrs303 <54661797+mrs303@users.noreply.github.com>
2024-02-29 09:17:45 +01:00
Karol Damaszke
212136dff8
Log exceptions to debug.log (#52) (#84)
Co-authored-by: madamczykhabana <110973826+madamczykhabana@users.noreply.github.com>
2024-02-29 09:14:42 +01:00
Karol Damaszke
c7ccfb87ff
Grouped pad/shift/move operations (#57) (#82)
Co-authored-by: madamczykhabana <110973826+madamczykhabana@users.noreply.github.com>
2024-02-29 04:16:44 +01:00
Karol Damaszke
2122acc60f
Add warmup for all possible shapes for prefill #49 (#81) 2024-02-28 10:40:13 +01:00
Karol Damaszke
31bed905d4
Update habana profiler (#50) (#80)
Co-authored-by: mswiniarsk <156412439+mswiniarsk@users.noreply.github.com>
2024-02-28 09:57:40 +01:00
Karol Damaszke
d31fb62576
Add more info to high-level profiler events (#46) (#79)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-02-28 09:55:50 +01:00
Karol Damaszke
941d36f3fd
Enable deferred token generation (#44) (#75)
Co-authored-by: Krzysztof Laskowski <klaskowski@habana.ai>
2024-02-27 15:46:40 +01:00
jkaniecki
83b059bd27
Bulk shifting (#40) (#70)
Co-authored-by: madamczykhabana <110973826+madamczykhabana@users.noreply.github.com>
2024-02-26 17:29:56 +01:00
jkaniecki
c3bd8ef445
Add Fp8 support (#42) (#71)
Co-authored-by: mrs303 <54661797+mrs303@users.noreply.github.com>
Co-authored-by: Adam Stachowicz <105052242+astachowiczhabana@users.noreply.github.com>
Co-authored-by: Grzegorz Morys <gmorys@habana.ai>
2024-02-23 11:52:28 +01:00
jkaniecki
a490847702
Sequence bucketing for prefill (#39) (#67)
Co-authored-by: mswiniarsk <156412439+mswiniarsk@users.noreply.github.com>
2024-02-23 01:52:14 +01:00
jkaniecki
9ad6086250
Improve habana profile dev experience (#36) (#65)
Co-authored-by: Michal Szutenberg <37601244+szutenberg@users.noreply.github.com>
2024-02-22 13:57:45 +01:00
jkaniecki
f7ef414e38
Remove unused pad_token_id for filter (#35) (#64)
Co-authored-by: mswiniarsk <156412439+mswiniarsk@users.noreply.github.com>
2024-02-22 11:24:09 +01:00
jkaniecki
8f590759e3
Prefill optimization by allocating space only for the first output token (#34) (#62)
Co-authored-by: mswiniarsk <156412439+mswiniarsk@users.noreply.github.com>
Co-authored-by: Karol Damaszke <karol.damaszke@intel.com>
2024-02-22 04:55:43 +01:00
jkaniecki
80303b469c
Do not limit hpu graphs by default (#32) (#61)
Co-authored-by: mswiniarsk <156412439+mswiniarsk@users.noreply.github.com>
2024-02-21 15:38:00 +01:00
jkaniecki
6b6dec9ea1
Transparent tokenizer uses explicit int32 (#31) (#60)
Co-authored-by: Adam Stachowicz <105052242+astachowiczhabana@users.noreply.github.com>
2024-02-21 14:24:41 +01:00
regisss
2060bb58bf
Fix trust remote code (#55) 2024-02-19 07:53:24 +01:00
Karol Damaszke
2a7a967de3
Revert prefill optimization and fix accuracy issue in shift operation (#29)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
Co-authored-by: madamczykhabana <110973826+madamczykhabana@users.noreply.github.com>
Co-authored-by: jkaniecki <153085639+jkaniecki@users.noreply.github.com>
2024-01-23 15:19:07 +01:00
jkaniecki
ac3bc0e95e
Removed kv_cache from HPU graph output (#19) 2024-01-19 15:34:13 +01:00
Karol Damaszke
60f63262db
Prefill optimization by allocating space only for the first token (#17) 2024-01-19 15:18:35 +01:00
Adam Stachowicz
0b96da89aa
Make tokenizer optional (#12) 2024-01-19 15:12:04 +01:00
madamczykhabana
381ec38cad
Batch bucketing improvements (#15) 2024-01-17 10:09:27 +01:00
mrs303
8523f7ef64
Deepspeed terminate (#11) 2024-01-17 09:57:03 +01:00
Krzysztof Laskowski
c459c86f88
High-level server profiler (#13) 2024-01-16 09:57:29 +01:00
madamczykhabana
41c4f4fa41
Debugging utils (#14) 2024-01-15 21:05:27 +01:00
Karol Damaszke
a8c5b69e2c
Set default value of LIMIT_HPU_GRAPH to True (#7) 2024-01-11 14:51:49 +01:00
Karol Damaszke
252ccde104
Control prefill and decode batch size separately (#6) 2024-01-02 18:21:01 +01:00
Karol Damaszke
1be2d9a8ec
Batch size bucketing (#5) 2023-12-22 21:53:01 +01:00
jkaniecki
e3dcd7f2c2
Disable tensor caching in HPU Graph execution (#4) 2023-12-22 13:51:16 +01:00
Karol Damaszke
6436ae86a1
Fix for continuous batching (#1) 2023-12-11 09:24:09 +01:00
regisss
e5f124b077 Merge tag 'v1.2.0' into v1.2-release 2023-12-06 18:46:16 +01:00
regisss
c09066aeb1 Merge tag 'v1.1.1' into v1.1-release 2023-12-06 09:50:58 +01:00
regisss
cc744ba426 Add changes from Optimum Habana's TGI folder 2023-12-05 11:12:16 +01:00
Nicolas Patry
ba552e1a82
Let each model resolve their own default dtype. (#1287)
# What does this PR do?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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Here are the
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2023-11-28 17:54:26 +01:00
fxmarty
b2b5df0e94
Add RoCm support (#1243)
This PR adds support for AMD Instinct MI210 & MI250 GPUs, with paged
attention and FAv2 support.

Remaining items to discuss, on top of possible others:
* Should we have a
`ghcr.io/huggingface/text-generation-inference:1.1.0+rocm` hosted image,
or is it too early?
* Should we set up a CI on MI210/MI250? I don't have access to the
runners of TGI though.
* Are we comfortable with those changes being directly in TGI, or do we
need a fork?

---------

Co-authored-by: Felix Marty <felix@hf.co>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: Your Name <you@example.com>
2023-11-27 14:08:12 +01:00
Nicolas Patry
ed2a3f617e
Exllama v2 (#1211)
# What does this PR do?

See #1165

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      Pull Request section?
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---------

Co-authored-by: Florian Zimmermeister <flozi00.fz@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-24-153.ec2.internal>
2023-11-25 22:38:38 +01:00
Vince Jankovics
c6bb76703f
Fix IDEFICS dtype (#1214)
# What does this PR do?

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This forces the use of `bfloat16` for IDEFICS. The issue is that with
`float16` the 80b model gives garbage output. Let me know if this
solution is not appropriate and I'll adjust accordingly. For the details
see below.

The current behaviour:
```sh
$ curl 127.0.0.1:8080/generate -X POST -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' -H 'Content-Type: application/json'
{"generated_text":""}
```

On closer inspection with:
```python
import requests

headers = { "Content-Type": "application/json"}

query = "What is Deep Learning?"
data = {
    "inputs": query,
    "parameters": {
        "max_new_tokens": 10,
        "return_full_text": True,
        "decoder_input_details": True,
        "do_sample": False,
    },
}

api_url = "http://127.0.0.1:8080"
response = requests.post(api_url + "/generate", headers=headers, json=data).json()

for i in ['prefill', 'tokens']:
    print(f'### {i}')
    print(repr(''.join([t['text'] for t in response['details'][i]])))
```

Prints:
```
### prefill
'<s>WhatisDeepLearning?'
### tokens
'<unk><unk><unk><unk><unk><unk><unk><unk><unk><unk>'
########
```

With the change in this PR it prints:
```
### prefill
'<s>WhatisDeepLearning?'
### tokens
'\n\nDeep Learning is a subset of machine'
```

Note, using the Transformers implementation (with
`IdeficsForVisionText2Text.from_pretrained`) produces the latter
(correct) output as well.
This only happens with the 80b model, the 9b model is not as sensitive
to the dtype (as also mentioned in the code).

The reason for "forcing" this in the IDEFICS init method, is because if
quantization is used, then the dtype cannot be set explicitly. And since
it's left as `None`, it's set to `float16` by default
[here](96a982ad8f/server/text_generation_server/models/__init__.py (L90)).
I.e. there's no other way to manually change the dtype if someone is
using quantization:
```sh
$ docker run .... ghcr.io/huggingface/text-generation-inference:latest --model-id HuggingFaceM4/idefics-80b-instruct --dtype bfloat16 --quantize bitsandbytes-nf4
.....
2023-10-31T12:42:26.710401Z  INFO shard-manager: text_generation_launcher: Starting shard rank=0
2023-10-31T12:42:30.315734Z ERROR shard-manager: text_generation_launcher: Shard complete standard error output:

Traceback (most recent call last):

  File "/opt/conda/bin/text-generation-server", line 8, in <module>
    sys.exit(app())

  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/cli.py", line 80, in serve
    raise RuntimeError(

RuntimeError: Only 1 can be set between `dtype` and `quantize`, as they both decide how goes the final model.
 rank=0
Error: ShardCannotStart
2023-10-31T12:42:30.414010Z ERROR text_generation_launcher: Shard 0 failed to start
2023-10-31T12:42:30.414044Z  INFO text_generation_launcher: Shutting down shards
```

## Before submitting
- [ ] 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?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.

@Narsil what do you think?

<!-- Your PR will be replied to more quickly if you can figure out the
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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-11-23 15:00:09 +01:00
Traun Leyden
e12c34bd25
Load PEFT weights from local directory (#1260)
# What does this PR do?

Enables PEFT weights to be loaded from a local directory, as opposed to
a hf hub repository. It is a continuation of the work in PR
https://github.com/huggingface/text-generation-inference/pull/762

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Fixes #1259 


## Before submitting
- [ ] 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? **Yes but I don't know how to run the tests for
this repo, and it doesn't look like this code is covered anyway**
- [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. **Yes, @Narsil asked for a PR in [this
comment](https://github.com/huggingface/text-generation-inference/pull/762#issuecomment-1728089505)**
- [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).
**I didn't see any documentation added to the [original
PR](https://github.com/huggingface/text-generation-inference/pull/762),
and am not sure where this belongs. Let me know and I can add some**
- [x] Did you write any new necessary tests? **I didn't see any existing
test coverage for this python module**


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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-11-23 12:56:17 +01:00
Diwank Singh Tomer
91111a0dc2
Fix missing trust_remote_code flag for AutoTokenizer in utils.peft (#1270)
Peft loading function was missing the
`trust_remote_code=trust_remote_code` argument causing the custom
tokenizer code to be not found.


## Before submitting
- [ ] 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?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.

@Narsil
2023-11-23 12:41:05 +01:00
OlivierDehaene
96a982ad8f fix: better warmup error 2023-10-25 10:18:58 +02:00
OlivierDehaene
12590fdcce
feat: paged attention v2 (#1183) 2023-10-23 12:29:25 +02:00