151 lines
5.6 KiB
Markdown
151 lines
5.6 KiB
Markdown
|
<p align="center">
|
|||
|
|
<picture>
|
|||
|
|
<!-- TODO: Replace tmp link to logo url after vllm-projects/vllm-ascend ready -->
|
|||
|
|
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/user-attachments/assets/4a958093-58b5-4772-a942-638b51ced646">
|
|||
|
|
<img alt="vllm-ascend" src="https://github.com/user-attachments/assets/838afe2f-9a1d-42df-9758-d79b31556de0" width=55%>
|
|||
|
|
</picture>
|
|||
|
|
</p>
|
|||
|
|
|
|||
|
|
<h3 align="center">
|
|||
|
|
vLLM Ascend Plugin
|
|||
|
|
</h3>
|
|||
|
|
|
|||
|
|
<p align="center">
|
|||
|
|
| <a href="https://www.hiascend.com/en/"><b>关于昇腾</b></a> | <a href="https://slack.vllm.ai"><b>开发者 Slack (#sig-ascend)</b></a> |
|
|||
|
|
</p>
|
|||
|
|
|
|||
|
|
<p align="center">
|
|||
|
|
<a href="README.md"><b>English</b></a> | <a><b>中文</b></a>
|
|||
|
|
</p>
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
*最新消息* 🔥
|
|||
|
|
|
|||
|
|
- [2024/12] 我们正在与 vLLM 社区合作，以支持 [[RFC]: Hardware pluggable](https://github.com/vllm-project/vllm/issues/11162).
|
|||
|
|
---
|
|||
|
|
## 总览
|
|||
|
|
|
|||
|
|
vLLM 昇腾插件 (`vllm-ascend`) 是一个让vLLM在Ascend NPU无缝运行的后端插件。
|
|||
|
|
|
|||
|
|
此插件是 vLLM 社区中支持昇腾后端的推荐方式。它遵循[[RFC]: Hardware pluggable](https://github.com/vllm-project/vllm/issues/11162)所述原则：通过解耦的方式提供了vLLM对Ascend NPU的支持。
|
|||
|
|
|
|||
|
|
使用 vLLM 昇腾插件，可以让类Transformer、混合专家(MOE)、嵌入、多模态等流行的大语言模型在 Ascend NPU 上无缝运行。
|
|||
|
|
|
|||
|
|
## 前提
|
|||
|
|
### 支持的设备
|
|||
|
|
- Atlas A2 训练系列 (Atlas 800T A2, Atlas 900 A2 PoD, Atlas 200T A2 Box16, Atlas 300T A2)
|
|||
|
|
- Atlas 800I A2 推理系列 (Atlas 800I A2)
|
|||
|
|
|
|||
|
|
### 依赖
|
|||
|
|
| 需求 | 支持的版本 | 推荐版本 | 注意 |
|
|||
|
|
|-------------|-------------------| ----------- |------------------------------------------|
|
|||
|
|
| vLLM | main | main | vllm-ascend 依赖 |
|
|||
|
|
| Python | >= 3.9 | [3.10](https://www.python.org/downloads/) | vllm 依赖 |
|
|||
|
|
| CANN | >= 8.0.RC2 | [8.0.RC3](https://www.hiascend.com/developer/download/community/result?module=cann&cann=8.0.0.beta1) | vllm-ascend and torch-npu 依赖 |
|
|||
|
|
| torch-npu | >= 2.4.0 | [2.5.1rc1](https://gitee.com/ascend/pytorch/releases/tag/v6.0.0.alpha001-pytorch2.5.1) | vllm-ascend 依赖 |
|
|||
|
|
| torch | >= 2.4.0 | [2.5.1](https://github.com/pytorch/pytorch/releases/tag/v2.5.1) | torch-npu and vllm 依赖 |
|
|||
|
|
|
|||
|
|
在[此处](docs/environment.zh.md)了解更多如何配置您环境的信息。
|
|||
|
|
|
|||
|
|
## 开始使用
|
|||
|
|
|
|||
|
|
> [!NOTE]
|
|||
|
|
> 目前，我们正在积极与 vLLM 社区合作以支持 Ascend 后端插件，一旦支持，您可以使用一行命令: `pip install vllm vllm-ascend` 来完成安装。
|
|||
|
|
|
|||
|
|
通过源码安装:
|
|||
|
|
```bash
|
|||
|
|
# 安装vllm main 分支参考文档:
|
|||
|
|
# https://docs.vllm.ai/en/latest/getting_started/installation/cpu/index.html#build-wheel-from-source
|
|||
|
|
git clone --depth 1 https://github.com/vllm-project/vllm.git
|
|||
|
|
cd vllm
|
|||
|
|
pip install -r requirements-build.txt
|
|||
|
|
VLLM_TARGET_DEVICE=empty pip install .
|
|||
|
|
|
|||
|
|
# 安装vllm-ascend main 分支
|
|||
|
|
git clone https://github.com/vllm-project/vllm-ascend.git
|
|||
|
|
cd vllm-ascend
|
|||
|
|
pip install -e .
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
运行如下命令使用 [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) 模型启动服务:
|
|||
|
|
|
|||
|
|
```bash
|
|||
|
|
# 设置环境变量 VLLM_USE_MODELSCOPE=true 加速下载
|
|||
|
|
vllm serve Qwen/Qwen2.5-0.5B-Instruct
|
|||
|
|
curl http://localhost:8000/v1/models
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
请参阅 [vLLM 快速入门](https://docs.vllm.ai/en/latest/getting_started/quickstart.html)以获取更多详细信息。
|
|||
|
|
|
|||
|
|
## 构建
|
|||
|
|
|
|||
|
|
#### 从源码构建Python包
|
|||
|
|
|
|||
|
|
```bash
|
|||
|
|
git clone https://github.com/vllm-project/vllm-ascend.git
|
|||
|
|
cd vllm-ascend
|
|||
|
|
pip install -e .
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
#### 构建容器镜像
|
|||
|
|
```bash
|
|||
|
|
git clone https://github.com/vllm-project/vllm-ascend.git
|
|||
|
|
cd vllm-ascend
|
|||
|
|
docker build -t vllm-ascend-dev-image -f ./Dockerfile .
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
查看[构建和测试](./CONTRIBUTING.zh.md)以获取更多详细信息，其中包含逐步指南，帮助您设置开发环境、构建和测试。
|
|||
|
|
|
|||
|
|
## 特性支持矩阵
|
|||
|
|
| Feature | Supported | Note |
|
|||
|
|
|---------|-----------|------|
|
|||
|
|
| Chunked Prefill | ✗ | Plan in 2025 Q1 |
|
|||
|
|
| Automatic Prefix Caching | ✅ | Imporve performance in 2025 Q1 |
|
|||
|
|
| LoRA | ✗ | Plan in 2025 Q1 |
|
|||
|
|
| Prompt adapter | ✅ ||
|
|||
|
|
| Speculative decoding | ✅ | Impore accuracy in 2025 Q1|
|
|||
|
|
| Pooling | ✗ | Plan in 2025 Q1 |
|
|||
|
|
| Enc-dec | ✗ | Plan in 2025 Q1 |
|
|||
|
|
| Multi Modality | ✅ (LLaVA/Qwen2-vl/Qwen2-audio/internVL)| Add more model support in 2025 Q1 |
|
|||
|
|
| LogProbs | ✅ ||
|
|||
|
|
| Prompt logProbs | ✅ ||
|
|||
|
|
| Async output | ✅ ||
|
|||
|
|
| Multi step scheduler | ✅ ||
|
|||
|
|
| Best of | ✅ ||
|
|||
|
|
| Beam search | ✅ ||
|
|||
|
|
| Guided Decoding | ✗ | Plan in 2025 Q1 |
|
|||
|
|
|
|||
|
|
## 模型支持矩阵
|
|||
|
|
|
|||
|
|
此处展示了部分受支持的模型。有关更多详细信息，请参阅 [supported_models](docs/supported_models.md)：
|
|||
|
|
| Model | Supported | Note |
|
|||
|
|
|---------|-----------|------|
|
|||
|
|
| Qwen 2.5 | ✅ ||
|
|||
|
|
| Mistral | | Need test |
|
|||
|
|
| DeepSeek v2.5 | |Need test |
|
|||
|
|
| LLama3.1/3.2 | ✅ ||
|
|||
|
|
| Gemma-2 | |Need test|
|
|||
|
|
| baichuan | |Need test|
|
|||
|
|
| minicpm | |Need test|
|
|||
|
|
| internlm | ✅ ||
|
|||
|
|
| ChatGLM | ✅ ||
|
|||
|
|
| InternVL 2.5 | ✅ ||
|
|||
|
|
| Qwen2-VL | ✅ ||
|
|||
|
|
| GLM-4v | |Need test|
|
|||
|
|
| Molomo | ✅ ||
|
|||
|
|
| LLaVA 1.5 | ✅ ||
|
|||
|
|
| Mllama | |Need test|
|
|||
|
|
| LLaVA-Next | |Need test|
|
|||
|
|
| LLaVA-Next-Video | |Need test|
|
|||
|
|
| Phi-3-Vison/Phi-3.5-Vison | |Need test|
|
|||
|
|
| Ultravox | |Need test|
|
|||
|
|
| Qwen2-Audio | ✅ ||
|
|||
|
|
|
|||
|
|
|
|||
|
|
## 贡献
|
|||
|
|
我们欢迎并重视任何形式的贡献与合作：
|
|||
|
|
- 请通过[提交问题](https://github.com/vllm-project/vllm-ascend/issues)来告知我们您遇到的任何错误。
|
|||
|
|
- 请参阅 [CONTRIBUTING.zh.md](./CONTRIBUTING.zh.md) 中的贡献指南。
|
|||
|
|
## 许可证
|
|||
|
|
|
|||
|
|
Apache 许可证 2.0，如 [LICENSE](./LICENSE) 文件中所示。
|