update docker files
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
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61
README.md
61
README.md
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@ -383,10 +383,11 @@ source /usr/local/Ascend/ascend-toolkit/set_env.sh
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| torch-npu | 2.1.0 | 2.1.0.post3 |
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| deepspeed | 0.13.2 | 0.13.2 |
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Docker image:
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Docker users please refer to [Build Docker](#Build-Docker).
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- 32GB: [Download page](http://mirrors.cn-central-221.ovaijisuan.com/detail/130.html)
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- 64GB: [Download page](http://mirrors.cn-central-221.ovaijisuan.com/detail/131.html)
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**NOTE**
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The default docker image is [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). More options can be found at [cosdt/cann](https://hub.docker.com/r/cosdt/cann/tags).
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Remember to use `ASCEND_RT_VISIBLE_DEVICES` instead of `CUDA_VISIBLE_DEVICES` to specify the device to use.
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@ -426,7 +427,10 @@ llamafactory-cli webui
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#### Use Docker
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<details><summary>For NVIDIA GPU users:</summary>
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```bash
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cd ./docker/docker-cuda
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docker build -f ./Dockerfile \
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--build-arg INSTALL_BNB=false \
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--build-arg INSTALL_VLLM=false \
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@ -435,18 +439,63 @@ docker build -f ./Dockerfile \
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-t llamafactory:latest .
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docker run -it --gpus=all \
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-v ./hf_cache:/root/.cache/huggingface/ \
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-v ./data:/app/data \
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-v ./output:/app/output \
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-v /$(dirname $(dirname "$PWD"))/hf_cache:/root/.cache/huggingface/ \
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-v /$(dirname $(dirname "$PWD"))/data:/app/data \
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-v /$(dirname $(dirname "$PWD"))/output:/app/output \
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-p 7860:7860 \
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-p 8000:8000 \
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--shm-size 16G \
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--name llamafactory \
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llamafactory:latest
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```
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</details>
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<details><summary>For Ascend NPU users:</summary>
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```bash
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cd ./docker/docker-npu
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docker build -f ./Dockerfile \
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--build-arg INSTALL_DEEPSPEED=false \
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--build-arg PIP_INDEX=https://pypi.org/simple \
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-t llamafactory:latest .
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# add --device for multi-npu usage
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# or modify --device to change npu card
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docker run -it \
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-v /$(dirname $(dirname "$PWD"))/hf_cache:/root/.cache/huggingface/ \
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-v /$(dirname $(dirname "$PWD"))/data:/app/data \
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-v /$(dirname $(dirname "$PWD"))/output:/app/output \
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-v /usr/local/dcmi:/usr/local/dcmi \
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-v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
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-v /usr/local/Ascend/driver/lib64:/usr/local/Ascend/driver/lib64 \
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-v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
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-v /etc/ascend_install.info:/etc/ascend_install.info \
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-p 7860:7860 \
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-p 8000:8000 \
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--device /dev/davinci0 \
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--device /dev/davinci_manager \
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--device /dev/devmm_svm \
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--device /dev/hisi_hdc \
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--shm-size 16G \
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--name llamafactory \
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llamafactory:latest
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```
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</details>
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#### Use Docker Compose
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Firstly enter your docker path:
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```bash
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# for NVIDIA GPU users
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cd ./docker/docker-cuda
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# for Ascend NPU users
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cd ./docker/docker-npu
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```
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Then run the following command to build docker image and start the container:
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```bash
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docker-compose up -d
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docker-compose exec llamafactory bash
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58
README_zh.md
58
README_zh.md
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@ -383,10 +383,11 @@ source /usr/local/Ascend/ascend-toolkit/set_env.sh
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| torch-npu | 2.1.0 | 2.1.0.post3 |
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| deepspeed | 0.13.2 | 0.13.2 |
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Docker 镜像:
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Docker用户请参考 [构建 Docker](#构建-Docker).
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- 32GB:[下载地址](http://mirrors.cn-central-221.ovaijisuan.com/detail/130.html)
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- 64GB:[下载地址](http://mirrors.cn-central-221.ovaijisuan.com/detail/131.html)
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**NOTE**
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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).
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请使用 `ASCEND_RT_VISIBLE_DEVICES` 而非 `CUDA_VISIBLE_DEVICES` 来指定运算设备。
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@ -426,7 +427,10 @@ llamafactory-cli webui
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#### 使用 Docker
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<details><summary>NVIDIA GPU 用户:</summary>
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```bash
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cd ./docker/docker-cuda
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docker build -f ./Dockerfile \
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--build-arg INSTALL_BNB=false \
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--build-arg INSTALL_VLLM=false \
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@ -435,18 +439,60 @@ docker build -f ./Dockerfile \
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-t llamafactory:latest .
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docker run -it --gpus=all \
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-v ./hf_cache:/root/.cache/huggingface/ \
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-v ./data:/app/data \
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-v ./output:/app/output \
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-v /$(dirname $(dirname "$PWD"))/hf_cache:/root/.cache/huggingface/ \
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-v /$(dirname $(dirname "$PWD"))/data:/app/data \
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-v /$(dirname $(dirname "$PWD"))/output:/app/output \
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-p 7860:7860 \
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-p 8000:8000 \
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--shm-size 16G \
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--name llamafactory \
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llamafactory:latest
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```
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</details>
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<details><summary>Ascend NPU 用户:</summary>
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```bash
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cd ./docker/docker-npu
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docker build -f ./Dockerfile \
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--build-arg INSTALL_DEEPSPEED=false \
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--build-arg PIP_INDEX=https://pypi.org/simple \
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-t llamafactory:latest .
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# 增加 --device 来使用多卡 NPU 或修改第一个 --device 来更改 NPU 卡
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docker run -it \
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-v /$(dirname $(dirname "$PWD"))/hf_cache:/root/.cache/huggingface/ \
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-v /$(dirname $(dirname "$PWD"))/data:/app/data \
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-v /$(dirname $(dirname "$PWD"))/output:/app/output \
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-v /usr/local/dcmi:/usr/local/dcmi \
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-v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
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-v /usr/local/Ascend/driver/lib64:/usr/local/Ascend/driver/lib64 \
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-v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
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-v /etc/ascend_install.info:/etc/ascend_install.info \
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-p 7860:7860 \
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-p 8000:8000 \
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--device /dev/davinci0 \
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--device /dev/davinci_manager \
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--device /dev/devmm_svm \
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--device /dev/hisi_hdc \
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--shm-size 16G \
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--name llamafactory \
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llamafactory:latest
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```
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</details>
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#### 使用 Docker Compose
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首先进入 docker 目录:
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```bash
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# NVIDIA GPU 用户
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cd ./docker/docker-cuda
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# Ascend NPU 用户
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cd ./docker/docker-npu
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```
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然后运行以下命令创建 docker 镜像并启动容器:
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```bash
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docker-compose up -d
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docker-compose exec llamafactory bash
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@ -9,16 +9,18 @@ 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
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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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# 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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RUN python -m pip install --upgrade pip
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RUN 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="metrics"; \
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@ -10,9 +10,9 @@ services:
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PIP_INDEX: https://pypi.org/simple
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container_name: llamafactory
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volumes:
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- ./hf_cache:/root/.cache/huggingface/
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- ./data:/app/data
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- ./output:/app/output
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- ../../hf_cache:/root/.cache/huggingface/
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- ../../data:/app/LLaMA-Factory/data
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- ../../output:/app/LLaMA-Factory/output
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ports:
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- "7860:7860"
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- "8000:8000"
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@ -0,0 +1,40 @@
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# 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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@ -0,0 +1,31 @@
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services:
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llamafactory:
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build:
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dockerfile: Dockerfile
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context: .
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args:
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INSTALL_DEEPSPEED: false
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PIP_INDEX: https://pypi.org/simple
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container_name: llamafactory
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volumes:
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- ../../hf_cache:/root/.cache/huggingface/
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- ../../data:/app/LLaMA-Factory/data
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- ../../output:/app/LLaMA-Factory/output
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- /usr/local/dcmi:/usr/local/dcmi
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- /usr/local/bin/npu-smi:/usr/local/bin/npu-smi
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- /usr/local/Ascend/driver/lib64:/usr/local/Ascend/driver/lib64
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- /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info
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- /etc/ascend_install.info:/etc/ascend_install.info
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ports:
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- "7860:7860"
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- "8000:8000"
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ipc: host
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tty: true
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stdin_open: true
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command: bash
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devices:
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- /dev/davinci0
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- /dev/davinci_manager
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- /dev/devmm_svm
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- /dev/hisi_hdc
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restart: unless-stopped
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