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# <div align="center"><strong>vLLM</strong></div>
## 简介
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vLLM是一个快速且易于使用的LLM推理和服务库,使用PageAttention高效管理kv内存,Continuous batching传入请求,支持很多Hugging Face模型,如LLaMA & LLaMA-2、Qwen、Chatglm2 & Chatglm3等。
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## 暂不支持的官方功能
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- **量化推理**:目前支持fp16的推理和gptq,awq-int4推理,mralin的权重量化、kv-cache fp8推理方案暂不支持
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- **模块支持**:目前不支持Sliding window attention
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## 支持模型结构列表
|     结构     |     模型      | 模型并行 | FP16 |
| :----------: | :----------: | :------: | :--: |
|    LlamaForCausalLM       |    LLaMA          |   Yes    | Yes  |
|    LlamaForCausalLM       |    LLaMA-2        |   Yes    | Yes  |
|    LlamaForCausalLM       |    LLaMA-3        |   Yes    | Yes  |
|    LlamaForCausalLM       |    Codellama      |   Yes    | Yes  |
|    QWenLMHeadModel        |    QWen           |   Yes    | Yes  |
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|    Qwen2ForCausalLM       |    QWen1.5        |   Yes    | Yes  |
|    Qwen2ForCausalLM       |    CodeQwen1.5    |   Yes    | Yes  |
|    Qwen2ForCausalLM       |    QWen2          |   Yes    | Yes  |
|    ChatGLMModel           |    chatglm2       |   Yes    | Yes  |
|    ChatGLMModel           |    chatglm3       |   Yes    | Yes  |
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|    BaiChuanForCausalLM    |    Baichuan       |   Yes    | Yes  |
|    BaiChuanForCausalLM    |    Baichuan2      |   Yes    | Yes  |
|    BloomForCausalLM       |    BLOOM          |   Yes    | Yes  |
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|    InternLMForCausalLM    |    InternLM       |   Yes    | Yes  |
|    InternLM2ForCausalLM   |    InternLM2      |   Yes    | Yes  |
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|    LlamaForCausalLM       |    deepseek       |   Yes    | Yes  |
|    DeepseekV2ForCausalLM  |    DeepSeek-V2    |   Yes    | Yes  |
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|    LlamaForCausalLM       |    Yi             |   Yes    | Yes  |
|    MixtralForCausalLM     |    Mixtral-8x7B   |   Yes    | Yes  |


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## 安装
vLLM支持
+ Python 3.8.
+ Python 3.9.
+ Python 3.10.
+ Python 3.11.
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### 使用源码编译方式安装
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#### 编译环境准备
提供2种环境准备方式:
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1. 基于光源pytorch2.3.0基础镜像环境:镜像下载地址:[https://sourcefind.cn/#/image/dcu/pytorch](https://sourcefind.cn/#/image/dcu/pytorch),根据pytorch2.1.0、python、dtk及系统下载对应的镜像版本。
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2. 基于现有python环境:安装pytorch2.3.0,pytorch whl包下载目录:[https://cancon.hpccube.com:65024/4/main/pytorch](https://cancon.hpccube.com:65024/4/main/pytorch),根据python、dtk版本,下载对应pytorch2.1.0的whl包。安装命令如下:
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```shell
pip install torch* (下载的torch的whl包)
pip install setuptools wheel
```
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#### 源码编译安装
```shell
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git clone http://developer.hpccube.com/codes/OpenDAS/vllm.git # 根据需要的分支进行切换
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```
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安装依赖:
```shell
pip install -r requirements-rocm.txt
```
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- 提供2种源码编译方式(进入vllm目录):
```
1. 编译whl包并安装
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VLLM_INSTALL_PUNICA_KERNELS=1 python setup.py bdist_wheel 
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cd dist
pip install vllm*
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2. 源码编译安装
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VLLM_INSTALL_PUNICA_KERNELS=1 python3 setup.py install 
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```
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#### 运行基础环境准备
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1、使用上面基于光源pytorch2.3.0基础镜像环境
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2、根据pytorch2.3.0、python、dtk及系统下载对应的依赖包:
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- triton:[https://cancon.hpccube.com:65024/4/main/triton](https://cancon.hpccube.com:65024/4/main/triton/)
- xformers:[https://cancon.hpccube.com:65024/4/main/xformers](https://cancon.hpccube.com:65024/4/main/xformers)
- flash_attn: [https://cancon.hpccube.com:65024/4/main/flash_attn](https://cancon.hpccube.com:65024/4/main/flash_attn)
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- lmslim: [https://cancon.hpccube.com:65024/4/main/lmslim](https://cancon.hpccube.com:65024/4/main/lmslim)
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#### 注意事项
+ 若使用 pip install 下载安装过慢,可添加源:-i https://pypi.tuna.tsinghua.edu.cn/simple/
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## 验证
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- python -c "import vllm; print(vllm.\_\_version__)",版本号与官方版本同步,查询该软件的版本号,例如0.6.1.post2;
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## Known Issue
-
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## 参考资料
- [README_ORIGIN](README_ORIGIN.md)
- [https://github.com/vllm-project/vllm](https://github.com/vllm-project/vllm)