mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-11-04 18:02:19 +08:00
096869c7b6
Note that the flash-attn library is installed in this image and the qwen model will use it automatically. However, if the the host machine's GPU is not compatible with the library, an exception will be raised during the training process as follows: FlashAttention only supports Ampere GPUs or newer. So if the --flash_attn flag is not set, an additional patch for the qwen model's config is necessary to set the default value of use_flash_attn from "auto" to False. Former-commit-id: cd2f5717d676e1a5afd2f4e7a38402d2e55e7479
15 lines
307 B
Docker
15 lines
307 B
Docker
FROM nvcr.io/nvidia/pytorch:24.01-py3
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WORKDIR /app
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COPY requirements.txt /app/
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RUN pip install -r requirements.txt
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COPY . /app/
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RUN pip install -e .[deepspeed,metrics,bitsandbytes,qwen]
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VOLUME [ "/root/.cache/huggingface/", "/app/data", "/app/output" ]
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EXPOSE 7860
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CMD [ "python", "src/train_web.py" ]
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