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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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co-authored by wangtiance gemini-code-assist[bot]
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docs/references/mindspore_models.md
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## Introduction ## 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 ## Requirements
MindSpore with SGLang current only support Ascend Npu device, users need first install Ascend CANN software packages. MindSpore currently only supports Ascend NPU devices. Users need to 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) 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 ## Supported Models
Currently, the following models are supported: 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...* - *More models coming soon...*
## Installation ## Installation
@@ -26,22 +27,23 @@ cd sgl-mindspore
pip install -e . 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 ```shell
pip install mindspore pip install "mindspore==2.7.1"
pip install "torch>=2.7.1" pip install "torch==2.8"
pip install "torch_npu>=2.7.1" pip install "torch_npu==2.8"
pip install triton_ascend pip install triton_ascend
``` ```
```shell ```shell
cp python/pyproject_other.toml python/pyproject.toml
pip install -e "python[all_npu]" pip install -e "python[all_npu]"
``` ```
## Run Model ## 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 ### Offline infer