Yikun Jiang 96d6fa7c90 [Docker] Fix openEuler image suffix (#586)
### What this PR does / why we need it?
There was a bug when we release v0.8.4rc1 (openEuler image tag was wrong
set to 0.8.4rc1), according doc of docker-meta-action, it should be
append suffix:
```
tags: |
  type=pep440,enable=true,priority=900,prefix=,suffix=,pattern=,value=
```

This patch just fix openEuler image suffix to make pep440 tag rule work.

This patch also remove the cache step because the cache step bring more
than 10mins export, but reduce less time in next trigger.

### Does this PR introduce _any_ user-facing change?
Yes, docker image tag set to right

### How was this patch tested?
I test with in my fork repo by setting default branch:
- release a tag: v0.7.88rc1 (pep440 tag)
- The log show `--label
org.opencontainers.image.version=v0.7.88rc1-openeuler` is right rule


https://github.com/Yikun/vllm-ascend/actions/runs/14560411481/job/40842950165#step:9:205

Related: https://github.com/vllm-project/vllm-ascend/pull/489

Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
2025-04-21 08:55:26 +08:00
2025-02-05 10:53:12 +08:00
2025-01-29 02:44:13 -08:00
2025-04-16 09:28:58 +08:00
2025-04-12 10:24:53 +08:00
2025-04-01 09:25:33 +08:00

vllm-ascend

vLLM Ascend Plugin

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

English | 中文


Latest News 🔥


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
    • CANN >= 8.0.0
    • PyTorch >= 2.5.1, torch-npu >= 2.5.1.dev20250320
    • 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:

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 0.8.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

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%