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[deps] Update pyproject.toml and requirements (#9714)

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Co-authored-by: Yaowei Zheng <hiyouga@buaa.edu.cn>
This commit is contained in:
jiaqiw09
2026-01-04 19:52:16 +08:00
committed by GitHub
parent 8600530002
commit 81b8a50aa5
32 changed files with 53 additions and 68 deletions
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README.md
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@@ -517,10 +517,11 @@ huggingface-cli login
```bash
git clone --depth 1 https://github.com/hiyouga/LLaMA-Factory.git
cd LLaMA-Factory
pip install -e ".[metrics]"
pip install -e .
pip install -r requirements/metrics.txt
```
Optional dependencies available: `metrics`, `deepspeed`. Install with: `pip install -e ".[metrics,deepspeed]"`
Optional dependencies available: `metrics`, `deepspeed`. Install with: `pip install -e . && pip install -r requirements/metrics.txt -r requirements/deepspeed.txt`
Additional dependencies for specific features are available in `examples/requirements/`.
@@ -578,36 +579,21 @@ To enable FlashAttention-2 on the Windows platform, please use the script from [
<details><summary>For Ascend NPU users</summary>
To install LLaMA Factory on Ascend NPU devices, please upgrade Python to version 3.10 or higher: `pip install -e . torch-npu==2.7.1`. Additionally, you need to install the **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**. Please follow the [installation tutorial](https://www.hiascend.com/document/detail/en/CANNCommunityEdition/600alphaX/softwareinstall/instg/atlasdeploy_03_0031.html) or use the following commands:
To install LLaMA Factory on Ascend NPU devices, please upgrade Python to version 3.10 or higher: `pip install -r requirements/npu.txt`. Additionally, you need to install the **Ascend CANN Toolkit and Kernels**. Please follow the [installation tutorial](https://llamafactory.readthedocs.io/en/latest/advanced/npu_installation.html).
You can also download the pre-built Docker images:
```bash
# replace the url according to your CANN version and devices
# install CANN Toolkit
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C20SPC702/Ascend-cann-toolkit_8.0.0.alpha002_linux-"$(uname -i)".run
bash Ascend-cann-toolkit_8.0.0.alpha002_linux-"$(uname -i)".run --install
# Docker Hub
docker pull hiyouga/llamafactory:latest-npu-a2
docker pull hiyouga/llamafactory:latest-npu-a3
# install CANN Kernels
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C20SPC702/Ascend-cann-kernels-910b_8.0.0.alpha002_linux-"$(uname -i)".run
bash Ascend-cann-kernels-910b_8.0.0.alpha002_linux-"$(uname -i)".run --install
# set env variables
source /usr/local/Ascend/ascend-toolkit/set_env.sh
# quay.io
docker pull quay.io/ascend/llamafactory:latest-npu-a2
docker pull quay.io/ascend/llamafactory:latest-npu-a3
```
| Requirement | Minimum | Recommend |
| ------------ | ------- | -------------- |
| CANN | 8.0.RC1 | 8.0.0.alpha002 |
| torch | 2.1.0 | 2.7.1 |
| torch-npu | 2.1.0 | 2.7.1 |
| deepspeed | 0.13.2 | 0.13.2 |
| vllm-ascend | - | 0.7.3 |
Remember to use `ASCEND_RT_VISIBLE_DEVICES` instead of `CUDA_VISIBLE_DEVICES` to specify the device to use.
If you cannot infer model on NPU devices, try setting `do_sample: false` in the configurations.
Download the pre-built Docker images: [32GB](http://mirrors.cn-central-221.ovaijisuan.com/detail/130.html) | [64GB](http://mirrors.cn-central-221.ovaijisuan.com/detail/131.html)
#### Install BitsAndBytes
To use QLoRA based on bitsandbytes on Ascend NPU, please follow these 3 steps: