mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-08-22 22:02:51 +08:00
3b499948a5
1. add docker-npu (Dockerfile and docker-compose.yml) 2. move cuda docker to docker-cuda and tiny changes to adapt to the new path Former-commit-id: d7207e8ad10c7df6dcb1f5e59ff8eb06f9d77e67
41 lines
1.1 KiB
Docker
41 lines
1.1 KiB
Docker
# Using ubuntu 22.04 images with cann 8.0.rc1
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# More options can be found at https://hub.docker.com/r/cosdt/cann/tags
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FROM cosdt/cann:8.0.rc1-910b-ubuntu22.04
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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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# Set the working directory
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WORKDIR /app/LLaMA-Factory
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RUN cd /app && \
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git config --global http.version HTTP/1.1 && \
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git clone https://github.com/hiyouga/LLaMA-Factory.git && \
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cd /app/LLaMA-Factory
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RUN pip config set global.index-url $PIP_INDEX
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RUN python3 -m pip install --upgrade pip
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# Install the LLaMA Factory
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RUN EXTRA_PACKAGES="torch-npu,metrics"; \
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if [ "$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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pip uninstall -y transformer-engine flash-attn
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# Set up volumes
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VOLUME [ "/root/.cache/huggingface/", "/app/data", "/app/output" ]
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# Expose port 7860 for the LLaMA Board
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EXPOSE 7860
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# Expose port 8000 for the API service
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EXPOSE 8000
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# Launch LLaMA Board
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CMD [ "llamafactory-cli", "webui" ]
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