diff --git a/README_zh.md b/README_zh.md index 6326c0b5..3bed0846 100644 --- a/README_zh.md +++ b/README_zh.md @@ -360,7 +360,7 @@ pip install https://github.com/jllllll/bitsandbytes-windows-webui/releases/downl
昇腾 NPU 用户指南 -在昇腾 NPU 设备上安装 LLaMA Factory 时,需要指定额外依赖项,使用 `pip install -e '.[torch-npu,metrics]'` 命令安装。此外,还需要安装 **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**,安装方法请参考[安装教程](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha002/quickstart/quickstart/quickstart_18_0004.html)或使用以下命令: +在昇腾 NPU 设备上安装 LLaMA Factory 时,需要指定额外依赖项,使用 `pip install -e ".[torch-npu,metrics]"` 命令安装。此外,还需要安装 **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**,安装方法请参考[安装教程](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha002/quickstart/quickstart/quickstart_18_0004.html)或使用以下命令: ```bash # 请替换 URL 为 CANN 版本和设备型号对应的 URL @@ -383,12 +383,6 @@ source /usr/local/Ascend/ascend-toolkit/set_env.sh | torch-npu | 2.1.0 | 2.1.0.post3 | | deepspeed | 0.13.2 | 0.13.2 | -Docker用户请参考 [构建 Docker](#构建-Docker). - -**NOTE** - -默认镜像为 [cosdt/cann:8.0.rc1-910b-ubuntu22.04](https://hub.docker.com/layers/cosdt/cann/8.0.rc1-910b-ubuntu22.04/images/sha256-29ef8aacf6b2babd292f06f00b9190c212e7c79a947411e213135e4d41a178a9?context=explore). 更多选择见 [cosdt/cann](https://hub.docker.com/r/cosdt/cann/tags). - 请使用 `ASCEND_RT_VISIBLE_DEVICES` 而非 `CUDA_VISIBLE_DEVICES` 来指定运算设备。 如果遇到无法正常推理的情况,请尝试设置 `do_sample: false`。 @@ -425,49 +419,62 @@ llamafactory-cli webui ### 构建 Docker -#### 使用 Docker - -
NVIDIA GPU 用户: +CUDA 用户: ```bash -cd ./docker/docker-cuda -docker build -f ./Dockerfile \ +docker-compose -f ./docker/docker-cuda/docker-compose.yml up -d +docker-compose exec llamafactory bash +``` + +昇腾 NPU 用户: + +```bash +docker-compose -f ./docker/docker-npu/docker-compose.yml up -d +docker-compose exec llamafactory bash +``` + +
不使用 Docker Compose 构建 + +CUDA 用户: + +```bash +docker build -f ./docker/docker-cuda/Dockerfile \ --build-arg INSTALL_BNB=false \ --build-arg INSTALL_VLLM=false \ --build-arg INSTALL_DEEPSPEED=false \ --build-arg PIP_INDEX=https://pypi.org/simple \ -t llamafactory:latest . -docker run -it --gpus=all \ - -v /$(dirname $(dirname "$PWD"))/hf_cache:/root/.cache/huggingface/ \ - -v /$(dirname $(dirname "$PWD"))/data:/app/data \ - -v /$(dirname $(dirname "$PWD"))/output:/app/output \ +docker run -dit --gpus=all \ + -v ./hf_cache:/root/.cache/huggingface/ \ + -v ./data:/app/data \ + -v ./output:/app/output \ -p 7860:7860 \ -p 8000:8000 \ --shm-size 16G \ --name llamafactory \ llamafactory:latest -``` -
-
Ascend NPU 用户: +docker exec -it llamafactory bash +``` + +昇腾 NPU 用户: ```bash -cd ./docker/docker-npu -docker build -f ./Dockerfile \ +# 根据您的环境选择镜像 +docker build -f ./docker/docker-npu/Dockerfile \ --build-arg INSTALL_DEEPSPEED=false \ --build-arg PIP_INDEX=https://pypi.org/simple \ -t llamafactory:latest . -# 增加 --device 来使用多卡 NPU 或修改第一个 --device 来更改 NPU 卡 -docker run -it \ - -v /$(dirname $(dirname "$PWD"))/hf_cache:/root/.cache/huggingface/ \ - -v /$(dirname $(dirname "$PWD"))/data:/app/data \ - -v /$(dirname $(dirname "$PWD"))/output:/app/output \ +# 根据您的资源更改 `device` +docker run -dit \ + -v ./hf_cache:/root/.cache/huggingface/ \ + -v ./data:/app/data \ + -v ./output:/app/output \ -v /usr/local/dcmi:/usr/local/dcmi \ -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \ - -v /usr/local/Ascend/driver/lib64:/usr/local/Ascend/driver/lib64 \ - -v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \ + -v /usr/local/Ascend/driver:/usr/local/Ascend/driver \ -v /etc/ascend_install.info:/etc/ascend_install.info \ -p 7860:7860 \ -p 8000:8000 \ @@ -478,26 +485,12 @@ docker run -it \ --shm-size 16G \ --name llamafactory \ llamafactory:latest + +docker exec -it llamafactory bash ``` +
-#### 使用 Docker Compose - -首先进入 docker 目录: -```bash -# NVIDIA GPU 用户 -cd ./docker/docker-cuda - -# Ascend NPU 用户 -cd ./docker/docker-npu -``` -然后运行以下命令创建 docker 镜像并启动容器: - -```bash -docker-compose up -d -docker-compose exec llamafactory bash -``` -
数据卷详情 - hf_cache:使用宿主机的 Hugging Face 缓存文件夹,允许更改为新的目录。