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Update MindSpore documentation (#13656)

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Co-authored-by: wangtiance <tiancew@qq.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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Tiance Wang
2025-11-24 11:20:51 +08:00
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docs/references/mindspore_models.md
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@@ -2,18 +2,19 @@
## Introduction
SGLang support run MindSpore framework models, this doc guide users to run mindspore models with SGLang.
MindSpore is a high-performance AI framework optimized for Ascend NPUs. This doc guides users to run MindSpore models in SGLang.
## Requirements
MindSpore with SGLang current only support Ascend Npu device, users need first install Ascend CANN software packages.
The CANN software packages can download from the [Ascend Official Websites](https://www.hiascend.com). The version depends on the MindSpore version [MindSpore Installation](https://www.mindspore.cn/install)
MindSpore currently only supports Ascend NPU devices. Users need to first install Ascend CANN software packages.
The CANN software packages can be downloaded from the [Ascend Official Website](https://www.hiascend.com). The recommended version is 8.3.RC1.
## Supported Models
Currently, the following models are supported:
- **Qwen3**: Dense models supported. MoE models coming soon.
- **Qwen3**: Dense and MoE models
- **DeepSeek V3/R1**
- *More models coming soon...*
## Installation
@@ -26,22 +27,23 @@ cd sgl-mindspore
pip install -e .
```
You will need to install the following packages, due to the support of tensor conversion through `dlpack` on 3rd devices, the minimum version of `PyTorch` is 2.7.1
You will need to install the following packages.
```shell
pip install mindspore
pip install "torch>=2.7.1"
pip install "torch_npu>=2.7.1"
pip install "mindspore==2.7.1"
pip install "torch==2.8"
pip install "torch_npu==2.8"
pip install triton_ascend
```
```shell
cp python/pyproject_other.toml python/pyproject.toml
pip install -e "python[all_npu]"
```
## Run Model
Current SGLang-MindSpore support Qwen3 dense model, this doc uses Qwen3-8B as example.
Current SGLang-MindSpore supports Qwen3 and DeepSeek V3/R1 models. This doc uses Qwen3-8B as an example.
### Offline infer