94a52cf577
### What this PR does / why we need it? Add @jianzs as vLLM Ascend maintainer @jianzs ---- I would like to nominate Shoujian Zheng (@jianzs <https://github.com/jianzs>) as a maintainer, starting with my +1. - He focuses on the code quality and good design with solid reviews in P/D disaggregation and DeepSeek improvement area about 30+ high quality review, such as #issuecomment-2811764833, #discussion_r2069927605 and #pullrequestreview-2820996674. This is the most important reason why I nominated him, because helping community developers complete PRs with high quality and continuously ensure the quality of codebase is one of the important responsibilities of a maintainer. We believe he is a great addition. - Shoujian's main expertise is distributed inference. He has a lot of experience in production about AI infra. He has very good habits and explains in great detail all changes #issue-3023082580 anqd share results open: #issuecomment-2853140443. And High quality PR: #706, #774, #852. - Community Involvement: Active involved in community discussion, he is collaborative and helps the users solve problems, involved in 30+ PR and issue, such as #issuecomment-2911934292 and #issuecomment-2833523571. Reference: [1] https://vllm-ascend.readthedocs.io/en/latest/community/contributors.html [2] https://vllm-ascend.readthedocs.io/en/latest/community/governance.html Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
vLLM Ascend Plugin
| About Ascend | Documentation | #sig-ascend | Users Forum | Weekly Meeting |
English | 中文
Latest News 🔥
- [2025/03] We hosted the vLLM Beijing Meetup with vLLM team! Please find the meetup slides here.
- [2025/02] vLLM community officially created vllm-project/vllm-ascend repo for running vLLM seamlessly on the Ascend NPU.
- [2024/12] We are working with the vLLM community to support [RFC]: Hardware pluggable.
Overview
vLLM Ascend (vllm-ascend) is a community maintained hardware plugin for running vLLM seamlessly on the Ascend NPU.
It is the recommended approach for supporting the Ascend backend within the vLLM community. It adheres to the principles outlined in the [RFC]: Hardware pluggable, providing a hardware-pluggable interface that decouples the integration of the Ascend NPU with vLLM.
By using vLLM Ascend plugin, popular open-source models, including Transformer-like, Mixture-of-Expert, Embedding, Multi-modal LLMs can run seamlessly on the Ascend NPU.
Prerequisites
- Hardware: Atlas 800I A2 Inference series, Atlas A2 Training series
- OS: Linux
- Software:
- Python >= 3.9, < 3.12
- CANN >= 8.1.RC1
- PyTorch >= 2.5.1, torch-npu >= 2.5.1
- vLLM (the same version as vllm-ascend)
Getting Started
Please refer to QuickStart and Installation for more details.
Contributing
See CONTRIBUTING for more details, which is a step-by-step guide to help you set up development environment, build and test.
We welcome and value any contributions and collaborations:
- Please let us know if you encounter a bug by filing an issue
- Please use User forum for usage questions and help.
Branch
vllm-ascend has main branch and dev branch.
- main: main branch，corresponds to the vLLM main branch, and is continuously monitored for quality through Ascend CI.
- vX.Y.Z-dev: development branch, created with part of new releases of vLLM. For example,
v0.7.3-devis the dev branch for vLLMv0.7.3version.
Below is maintained branches:
| Branch | Status | Note |
|---|---|---|
| main | Maintained | CI commitment for vLLM main branch and vLLM 0.9.x branch |
| v0.7.1-dev | Unmaintained | Only doc fixed is allowed |
| v0.7.3-dev | Maintained | CI commitment for vLLM 0.7.3 version |
Please refer to Versioning policy for more details.
Weekly Meeting
- vLLM Ascend Weekly Meeting: https://tinyurl.com/vllm-ascend-meeting
- Wednesday, 15:00 - 16:00 (UTC+8, Convert to your timezone)
License
Apache License 2.0, as found in the LICENSE file.