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@ -107,10 +107,10 @@ pip install tensorboardX
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8.安装vllm(模型推理)
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8.安装vllm(模型推理)
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我们提供了python3.8、python3.10版本的vllm安装包,相关依赖均已封装,可直接安装后执行推理:
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我们提供python3.8、python3.10版本的vllm安装包,相关依赖均已封装,可直接安装后执行推理:
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[vllm-0.5.0.dev0+cu122-cp38-cp38-linux_x86_64.whl](https://qy-obs-6d58.obs.cn-north-4.myhuaweicloud.com/vllm-0.5.0.dev0%2Bcu122-cp38-cp38-linux_x86_64.whl)
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[vllm-0.5.0.dev0+cu122-cp38-cp38-linux_x86_64.whl](https://qy-obs-6d58.obs.cn-north-4.myhuaweicloud.com/vllm-0.5.0.dev0%2Bcu122-cp38-cp38-linux_x86_64.whl)
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[vllm-0.5.0.dev0+cu122-cp310-cp310-linux_x86_64.whl](https://qy-obs-6d58.obs.cn-north-4.myhuaweicloud.com/vllm-0.5.0.dev0%2Bcu122-cp310-cp310-linux_x86_64.whl)
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[vllm-0.5.0.dev0+cu122-cp310-cp310-linux_x86_64.whl](https://qy-obs-6d58.obs.cn-north-4.myhuaweicloud.com/vllm-0.5.0.dev0%2Bcu122-cp310-cp310-linux_x86_64.whl)
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同时,我们也提供了vllm源码,位于/quick_start_clean/tools/vllm-0.5.0.dev0.tar。
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同时,我们也提供了vllm源码,位于/quick_start_clean/tools/vllm-0.5.0.dev0.tar
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```
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```
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## 开源模型
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## 开源模型
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@ -461,6 +461,7 @@ llm = LLM(model="../models/8b_sft_model/", tokenizer_mode="cpm", trust_remote_co
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### 部署OpenAI API服务推理
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### 部署OpenAI API服务推理
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vLLM可以为 LLM 服务进行部署,这里提供了一个示例:
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vLLM可以为 LLM 服务进行部署,这里提供了一个示例:
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1. 启动服务:
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1. 启动服务:
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端侧2B模型:
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端侧2B模型:
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```shell
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```shell
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python -m vllm.entrypoints.openai.api_server \
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python -m vllm.entrypoints.openai.api_server \
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@ -485,7 +486,6 @@ python -m vllm.entrypoints.openai.api_server \
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```
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```
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执行对应指令后,默认在http://localhost:8000地址上启动服务,启动成功后终端会出现如下提示:
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执行对应指令后,默认在http://localhost:8000地址上启动服务,启动成功后终端会出现如下提示:
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```shell
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```shell
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INFO: Started server process [950965]
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INFO: Started server process [950965]
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INFO: Waiting for application startup.
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INFO: Waiting for application startup.
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@ -495,7 +495,6 @@ INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
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2. 调用API:
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2. 调用API:
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启动服务端成功后,重新打开一个终端,可参考执行以下python脚本:
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启动服务端成功后,重新打开一个终端,可参考执行以下python脚本:
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``` python
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``` python
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from openai import OpenAI
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from openai import OpenAI
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# 如果启动服务时指定了api密钥,需要修改为对应的密钥,否则为"EMPTY"
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# 如果启动服务时指定了api密钥,需要修改为对应的密钥,否则为"EMPTY"
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