From 75222bfed9201dda423d1e72d24c1aff3367a6f6 Mon Sep 17 00:00:00 2001 From: Tiance Wang Date: Mon, 24 Nov 2025 11:20:51 +0800 Subject: [PATCH] Update MindSpore documentation (#13656) Co-authored-by: wangtiance Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- docs/references/mindspore_models.md | 20 +++++++++++--------- 1 file changed, 11 insertions(+), 9 deletions(-) diff --git a/docs/references/mindspore_models.md b/docs/references/mindspore_models.md index 417cb94ad..80dd3b7f0 100644 --- a/docs/references/mindspore_models.md +++ b/docs/references/mindspore_models.md @@ -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