aidoczh c32eea96b7 [Doc]Add Chinese translation for documentation (#1870)
### What this PR does / why we need it?

This PR adds a complete Chinese translation for the documentation using
PO files and the gettext toolchain. The goal is to make the
documentation more accessible to Chinese-speaking users and help the
community grow.

### Does this PR introduce any user-facing change?

Yes. This PR introduces Chinese documentation, which users can access
alongside the original English documentation. No changes to the core
code or APIs.

### How was this patch tested?

The translated documentation was built locally using the standard
documentation build process (`make html` or `sphinx-build`). I checked
the generated HTML pages to ensure the Chinese content displays
correctly and matches the original structure. No code changes were made,
so no additional code tests are required.

vLLM version: v0.9.2  
vLLM main: vllm-project/vllm@5780121

---

Please review the translation and let me know if any improvements are
needed. I am happy to update the translation based on feedback.

- vLLM version: v0.9.2
- vLLM main:
7ba34b1241

---------

Signed-off-by: aidoczh <aidoczh@163.com>
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
Co-authored-by: Yikun Jiang <yikunkero@gmail.com>
2025-07-21 11:26:27 +08:00
2025-02-05 10:53:12 +08:00
2025-01-29 02:44:13 -08:00
2025-07-20 02:11:57 +08:00
2025-07-20 02:11:57 +08:00
2025-06-27 09:14:43 +08:00

vllm-ascend

vLLM Ascend Plugin

| About Ascend | Documentation | #sig-ascend | Users Forum | Weekly Meeting |

English | 中文


Latest News 🔥

  • [2025/06] User stories page is now live! It kicks off with LLaMA-Factory/verl//TRL/GPUStack to demonstrate how vLLM Ascend assists Ascend users in enhancing their experience across fine-tuning, evaluation, reinforcement learning (RL), and deployment scenarios.
  • [2025/06] Contributors page is now live! All contributions deserve to be recorded, thanks for all contributors.
  • [2025/05] We've released first official version v0.7.3! We collaborated with the vLLM community to publish a blog post sharing our practice: Introducing vLLM Hardware Plugin, Best Practice from Ascend NPU.
  • [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.post1.dev20250619
    • vLLM (the same version as vllm-ascend)

Getting Started

Please use the following recommended versions to get started quickly:

Version Release type Doc
v0.9.2rc1 Latest release candidate QuickStart and Installation for more details
v0.7.3.post1 Latest stable version 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:

Branch

vllm-ascend has main branch and dev branch.

  • main: main branchcorresponds 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-dev is the dev branch for vLLM v0.7.3 version.

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, only bug fix is allowed and no new release tag any more.
v0.9.1-dev Maintained CI commitment for vLLM 0.9.1 version

Please refer to Versioning policy for more details.

Weekly Meeting

License

Apache License 2.0, as found in the LICENSE file.

Description
XC-LLM: A Specially Optimized LLM Inference Engine for ModelHub XC
Readme Apache-2.0 8.6 MiB
Languages
Python 66.8%
C++ 31.8%
Shell 1%
CMake 0.2%
Dockerfile 0.1%
Other 0.1%