add Ascend npu doc and dependency

Former-commit-id: 803d9f142a294f8c1e0b4e2046c214b0857ccfd6
This commit is contained in:
MengqingCao
2024-05-28 01:33:54 +00:00
parent 26f293d587
commit e45a9d70fc
3 changed files with 39 additions and 2 deletions

View File

@@ -347,7 +347,25 @@ To enable FlashAttention-2 on the Windows platform, you need to install the prec
Join [NPU user group](assets/wechat_npu.jpg).
To utilize Ascend NPU devices for (distributed) training and inference, you need to install the **[torch-npu](https://gitee.com/ascend/pytorch)** library and the **[Ascend CANN Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**.
Use `pip install -e .[torch_npu]` to install LLaMA-Factory with **[torch-npu](https://gitee.com/ascend/pytorch)** library.
To utilize Ascend NPU devices for (distributed) training and inference, you need to install the **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**. You can follow chapter **[install CANN](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha002/quickstart/quickstart/quickstart_18_0004.html)** in the installation tutorial to install CANN Toolkit and the kernels, or use the fast installation as following:
```bash
# replace the url according to your choice
# install CANN Toolkit
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C17SPC701/Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run
chmod +x Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run
./Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run --install
# install CANN Kernels
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C18B800TP015/Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run
chmod +x Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run
./Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run --install
# set env variables
source /usr/local/Ascend/ascend-toolkit/set_env.sh
```
| Requirement | Minimum | Recommend |
| ------------ | ------- | --------- |