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update ascend docs (#17741)

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amote-i
2026-01-29 11:43:48 +08:00
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parent 0ff0d181ca
commit 1b22f2ee1c
2 changed files with 5 additions and 11 deletions
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10
docs/platforms/ascend_npu.md
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@@ -11,7 +11,6 @@ You can install SGLang using any of the methods below. Please go through `System
| Pytorch Adapter | 7.3.0 | [link](https://gitcode.com/Ascend/pytorch/releases) |
| MemFabric | 1.0.5 | `pip install memfabric-hybrid==1.0.5` |
| Triton | 3.2.0 | `pip install triton-ascend`|
| Bisheng | 20251121 | [link](https://sglang-ascend.obs.cn-east-3.myhuaweicloud.com/sglang/triton_ascend/Ascend-BiSheng-toolkit_aarch64_20251121.run) |
| SGLang NPU Kernel | NA | [link](https://github.com/sgl-project/sgl-kernel-npu/releases) |
<a id="obtain-cann-image"></a>
@@ -65,11 +64,6 @@ If you are using other versions of `torch` and install `torch_npu`, check [insta
We provide our own implementation of Triton for Ascend.
```shell
BISHENG_NAME="Ascend-BiSheng-toolkit_aarch64_20251121.run"
BISHENG_URL="https://sglang-ascend.obs.cn-east-3.myhuaweicloud.com/sglang/triton_ascend/${BISHENG_NAME}"
wget -O "${BISHENG_NAME}" "${BISHENG_URL}" && chmod a+x "${BISHENG_NAME}" && "./${BISHENG_NAME}" --install && rm "${BISHENG_NAME}"
```
```shell
pip install triton-ascend
```
@@ -112,8 +106,8 @@ You can download the SGLang image or build an image based on Dockerfile to obtai
dockerhub: docker.io/lmsysorg/sglang:$tag
# Main-based tag, change main to specific version like v0.5.6,
# you can get image for specific version
Atlas 800I A3 : {main}-cann8.3.rc2-a3
Atlas 800I A2: {main}-cann8.3.rc2-910b
Atlas 800I A3 : {main}-cann8.5.0-a3
Atlas 800I A2: {main}-cann8.5.0-910b
```
2. Build an image based on Dockerfile
```shell

6
docs/platforms/ascend_npu_support_models.md
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@@ -46,7 +46,7 @@ You are welcome to enable various models based on your business requirements.
| AI-ModelScope/dbrx-instruct | DBRX (Databricks) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| baichuan-inc/Baichuan2-13B-Chat | Baichuan 2 (7B, 13B) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| baidu/ERNIE-4.5-21B-A3B-PT | ERNIE-4.5 (4.5, 4.5MoE series) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| openbmb/MiniCPM3-4B | MiniCPM (v3, 4B) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| OpenBMB/MiniCPM3-4B | MiniCPM (v3, 4B) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| Kimi/Kimi-K2-Thinking | Kimi | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| openai/gpt-oss-120b | GPTOSS | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
@@ -74,7 +74,7 @@ You are welcome to enable various models based on your business requirements.
| lmms-lab/llava-onevision-qwen2-7b-ov | LLaVA-OneVision | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| Kimi/Kimi-VL-A3B-Instruct | Kimi-VL (A3B) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| ZhipuAI/GLM-4.5V | GLM-4.5V (106B) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| meta-llama/Llama-3.2-11B-Vision-Instruct | Llama 3.2 Vision (11B) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| LLM-Research/Llama-3.2-11B-Vision-Instruct | Llama 3.2 Vision (11B) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
## Embedding Models
@@ -95,7 +95,7 @@ You are welcome to enable various models based on your business requirements.
| Shanghai_AI_Laboratory/internlm2-7b-reward | InternLM 2 Reward | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| Qwen/Qwen2.5-Math-RM-72B | Qwen2.5 Reward - Math | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| Howeee/Qwen2.5-1.5B-apeach | Qwen2.5 Reward - Sequence | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| Skywork/Skywork-Reward-Gemma-2-27B-v0.2 | Gemma 2-27B Reward | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
| AI-ModelScope/Skywork-Reward-Gemma-2-27B-v0.2 | Gemma 2-27B Reward | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
## Rerank Models