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- # Use the NVIDIA official image with PyTorch 2.3.0
- # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-24-02.html
- FROM nvcr.io/nvidia/pytorch:24.02-py3
- # Define environments
- ENV MAX_JOBS=4
- ENV FLASH_ATTENTION_FORCE_BUILD=TRUE
- ENV VLLM_WORKER_MULTIPROC_METHOD=spawn
- # Define installation arguments
- ARG INSTALL_BNB=false
- ARG INSTALL_VLLM=false
- ARG INSTALL_DEEPSPEED=false
- ARG INSTALL_FLASHATTN=false
- ARG INSTALL_LIGER_KERNEL=false
- ARG INSTALL_HQQ=false
- ARG INSTALL_EETQ=false
- ARG PIP_INDEX=https://pypi.org/simple
- # Set the working directory
- WORKDIR /app
- # Install the requirements
- COPY requirements.txt /app
- RUN pip config set global.index-url "$PIP_INDEX" && \
- pip config set global.extra-index-url "$PIP_INDEX" && \
- python -m pip install --upgrade pip && \
- python -m pip install -r requirements.txt
- # Copy the rest of the application into the image
- COPY . /app
- # Install the LLaMA Factory
- RUN EXTRA_PACKAGES="metrics"; \
- if [ "$INSTALL_BNB" == "true" ]; then \
- EXTRA_PACKAGES="${EXTRA_PACKAGES},bitsandbytes"; \
- fi; \
- if [ "$INSTALL_VLLM" == "true" ]; then \
- EXTRA_PACKAGES="${EXTRA_PACKAGES},vllm"; \
- fi; \
- if [ "$INSTALL_DEEPSPEED" == "true" ]; then \
- EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \
- fi; \
- if [ "$INSTALL_LIGER_KERNEL" == "true" ]; then \
- EXTRA_PACKAGES="${EXTRA_PACKAGES},liger-kernel"; \
- fi; \
- if [ "$INSTALL_HQQ" == "true" ]; then \
- EXTRA_PACKAGES="${EXTRA_PACKAGES},hqq"; \
- fi; \
- if [ "$INSTALL_EETQ" == "true" ]; then \
- EXTRA_PACKAGES="${EXTRA_PACKAGES},eetq"; \
- fi; \
- pip install -e ".[$EXTRA_PACKAGES]"
- # Rebuild flash attention
- RUN pip uninstall -y transformer-engine flash-attn && \
- if [ "$INSTALL_FLASHATTN" == "true" ]; then \
- pip uninstall -y ninja && pip install ninja && \
- pip install --no-cache-dir flash-attn --no-build-isolation; \
- fi
- # Set up volumes
- VOLUME [ "/root/.cache/huggingface", "/root/.cache/modelscope", "/app/data", "/app/output" ]
- # Expose port 7860 for the LLaMA Board
- ENV GRADIO_SERVER_PORT 7860
- EXPOSE 7860
- # Expose port 8000 for the API service
- ENV API_PORT 8000
- EXPOSE 8000
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