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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 installation arguments | |
ARG INSTALL_BNB=false | |
ARG INSTALL_VLLM=false | |
ARG INSTALL_DEEPSPEED=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 $PIP_INDEX | |
RUN python -m pip install --upgrade pip | |
RUN python -m pip install -r requirements.txt | |
# Copy the rest of the application into the image | |
COPY . /app/ | |
# Install the LLaMA Factory | |
RUN EXTRA_PACKAGES="metrics"; \ | |
if [ "$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="${EXTRA_PACKAGES},deepspeed"; \ | |
fi; \ | |
pip install -e .[$EXTRA_PACKAGES] && \ | |
pip uninstall -y transformer-engine flash-attn | |
# Set up volumes | |
VOLUME [ "/root/.cache/huggingface/", "/app/data", "/app/output" ] | |
# Expose port 7860 for the LLaMA Board | |
EXPOSE 7860 | |
# Expose port 8000 for the API service | |
EXPOSE 8000 | |