mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-11-04 18:02:19 +08:00
46 lines
1.3 KiB
Docker
46 lines
1.3 KiB
Docker
# Use the Ubuntu 22.04 image with CANN 8.0.rc1
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# More versions can be found at https://hub.docker.com/r/cosdt/cann/tags
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# FROM cosdt/cann:8.0.rc1-910-ubuntu22.04
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FROM cosdt/cann:8.0.rc1-910b-ubuntu22.04
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# FROM cosdt/cann:8.0.rc1-910-openeuler22.03
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# FROM cosdt/cann:8.0.rc1-910b-openeuler22.03
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# Define environments
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ENV DEBIAN_FRONTEND=noninteractive
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# Define installation arguments
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ARG INSTALL_DEEPSPEED=false
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ARG PIP_INDEX=https://pypi.org/simple
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ARG TORCH_INDEX=https://download.pytorch.org/whl/cpu
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# Set the working directory
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WORKDIR /app
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# Install the requirements
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COPY requirements.txt /app
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RUN pip config set global.index-url "$PIP_INDEX" && \
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pip config set global.extra-index-url "$TORCH_INDEX" && \
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python -m pip install --upgrade pip && \
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python -m pip install -r requirements.txt
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# Copy the rest of the application into the image
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COPY . /app
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# Install the LLaMA Factory
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RUN EXTRA_PACKAGES="torch-npu,metrics"; \
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if [ "$INSTALL_DEEPSPEED" == "true" ]; then \
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EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \
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fi; \
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pip install -e ".[$EXTRA_PACKAGES]"
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# Set up volumes
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VOLUME [ "/root/.cache/huggingface", "/root/.cache/modelscope", "/app/data", "/app/output" ]
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# Expose port 7860 for the LLaMA Board
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ENV GRADIO_SERVER_PORT 7860
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EXPOSE 7860
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# Expose port 8000 for the API service
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ENV API_PORT 8000
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EXPOSE 8000
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