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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> |
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| .. | ||
| custom_modeling | ||
| __init__.py | ||
| bloom.py | ||
| cache_manager.py | ||
| causal_lm.py | ||
| flash_causal_lm.py | ||
| flash_llama.py | ||
| flash_mistral.py | ||
| flash_mixtral.py | ||
| flash_neox.py | ||
| flash_phi.py | ||
| flash_rw.py | ||
| flash_santacoder.py | ||
| galactica.py | ||
| gpt_neox.py | ||
| idefics_causal_lm.py | ||
| idefics.py | ||
| mamba.py | ||
| model.py | ||
| mpt.py | ||
| opt.py | ||
| phi.py | ||
| rw.py | ||
| santacoder.py | ||
| seq2seq_lm.py | ||
| t5.py | ||
| types.py | ||