• Nicolas Patry's avatar
    Add AWQ quantization inference support (#1019) (#1054) · c5de7cd8
    Nicolas Patry authored
    # 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?
    
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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?
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    [forum](https://discuss.huggingface.co/)? Please add a link
          to it if that's the case.
    - [ ] Did you make sure to update the documentation with your changes?
    Here are the
    [documentation
    guidelines](https://github.com/huggingface/transformers/tree/main/docs),
    and
    [here are tips on formatting
    docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation
    
    ).
    - [ ] Did you write any new necessary tests?
    
    
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    ---------
    Co-authored-by: default avatarAbhinav M Kulkarni <abhinavkulkarni@gmail.com>
    Co-authored-by: default avatarAbhinav Kulkarni <abhinav@concentric.ai>
    c5de7cd8
__init__.py 9.79 KB