44 lines
1.4 KiB
Plaintext
44 lines
1.4 KiB
Plaintext
以下内容都是在一体机上进行的：
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构建端口为7860的容器，设置端口和name
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docker run -p 7860:7860 \
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--name new_9g_finetuning \
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--env PATH=/usr/local/corex-4.0.0/bin:/usr/local/corex-4.0.0/lib64/python3/dist-packages/bin:/usr/local/openmpi/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin \
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--env DEBIAN_FRONTEND=noninteractive \
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--env COREX_VERSION=4.0.0 \
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--env LD_LIBRARY_PATH=/usr/local/corex-4.0.0/lib64:/usr/local/openmpi/lib:/usr/local/lib: \
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--env LANG=en_US.utf8 \
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--env LC_ALL=en_US.utf8 \
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--env PYTHONPATH=/usr/local/corex-4.0.0/lib64/python3/dist-packages \
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--env RUSTUP_DIST_SERVER=https://mirrors.ustc.edu.cn/rust-static \
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--env RUSTUP_UPDATE_ROOT=https://mirrors.ustc.edu.cn/rust-static/rustup \
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-v /data:/workspace \
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--cap-add ALL \
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--cgroupns host \
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--pid host \
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--privileged \
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--security-opt label=disable \
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9g_finetuning/lora:v3 \
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sleep infinity
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安装相关依赖
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pip install gradio_client
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可能报错，解决方法
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pip install importlib-metadata==4.13.0
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pip install --upgrade pip setuptools wheel
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推理
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a)打开系统终端，
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b)进入root模式:sudo su
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docker start new_9g_finetuning
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c)
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docker exec -it new_9g_finetuning /bin/bash
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d)
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cd /workspace/zksc/LLaMA-Factory
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e)输入
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CUDA_VISIBLE_DEVICES=0 llamafactory-cli webchat examples/inference/fm9g_merge.yaml
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f)最后执行推理代码生成回答文件
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