## 1. 瀚博半导体 ![vastaitech](https://github.com/Vastai/VastModelZOO/blob/main/images/index/logo.png?raw=true) - 官方网址:https://www.vastaitech.com - 模型中心:https://github.com/Vastai/VastModelZOO ## 2. 测试平台 - 以下为本指南测试使用的平台信息,供参考 ``` os: Ubuntu-22.04.3-LTS-x86_64 cpu: Hygon C86-4G gpu: VA16 / VA1L / VA10L torch: 2.8.0+cpu torch-vacc: 1.3.3.777 vllm: 0.11.1.dev0+gb8b302cde.d20251030.cpu vllm-vacc: 0.11.0.777 driver: 00.25.12.30 d3_3_v2_9_a3_1 a76bf37 20251230 docker: 28.1.1 ``` ## 3. 环境准备 - 获取vllm_vacc基础镜像 ```bash sudo docker pull harbor.vastaitech.com/ai_deliver/vllm_vacc:VVI-25.12.SP2 ``` - 启动容器 ```bash sudo docker run -it \ --privileged=true \ --shm-size=256g \ --name vllm_service \ --ipc=host \ --network=host \ harbor.vastaitech.com/ai_deliver/vllm_vacc:VVI-25.12.SP2 bash ``` - 安装MinerU - 参考官方文档安装:[README_zh-CN.md#安装-mineru](https://github.com/opendatalab/MinerU/blob/master/README_zh-CN.md#安装-mineru) ```bash # 启动容器 # sudo docker exec -it vllm_service bash # 可选pypi源 # https://mirrors.163.com/pypi/simple/ # https://mirrors.aliyun.com/pypi/simple/ # https://pypi.mirrors.ustc.edu.cn/simple/ # https://pypi.tuna.tsinghua.edu.cn/simple/ # https://mirror.baidu.com/pypi/simple # 通过源码安装MinerU git clone https://github.com/opendatalab/MinerU.git git checkout 8c4b3ef3a20b11ddac9903f25124d24ea82639b5 pip install -e .[core] -i https://mirrors.aliyun.com/pypi/simple # 或使用pip安装MinerU pip install -U "mineru[core]==2.7.0" -i https://mirrors.aliyun.com/pypi/simple ``` > [!NOTE] > - `vllm_vacc`基础镜像内已包含`torch/vllm`等相关依赖 > - 截至`2025/12/31`,`VastAI`已支持`MinerU`至最新版本`2.7.0`,`master分支8c4b3ef3` > - 和`NVIDIA`硬件下`CUDA_VISIBLE_DEVICES`类似;在`VastAI`硬件中可以使用`VACC_VISIBLE_DEVICES`指定`可见计算卡ID`,如`-e VACC_VISIBLE_DEVICES=0,1,2,3` > - 需指定适当的`--shm-size`虚拟内存 ## 4. MinerU功能 > [!NOTE] > - `VastAI`加速卡仅支持使用`vlm-auto-engine`和`vlm-http-client`形式进行`VLM`模型推理加速 - 进入容器 ```bash sudo docker exec -it vllm_service bash ``` - 使用MinerU - 模型准备,参考官方介绍:[model_source.md](https://github.com/opendatalab/MinerU/blob/master/docs/zh/usage/model_source.md) - 方式一:`vlm-auto-engine` ```bash export MINERU_MODEL_SOURCE=modelscope # step1, 以`vlm-auto-engine`方式启动MinerU解析任务 mineru -p image.png \ -o ./output \ -b vlm-auto-engine \ --http-timeout 1200 \ --tensor-parallel-size 2 \ --enforce_eager \ --trust-remote-code \ --max-model-len 16384 ``` - 方式二:`vlm-http-client` ```bash # step1, 启动vLLM API server vllm serve /root/.cache/modelscope/hub/models/OpenDataLab/MinerU2.5-2509-1.2B \ --tensor-parallel-size 2 \ --trust-remote-code \ --enforce_eager \ --port 8090 \ --max-model-len 16384 \ --served-model-name MinerU2.5-2509-1.2B # step2,以`vlm-http-client`方式启动MinerU解析任务 mineru -p demo/pdfs/demo1.pdf \ -o ./output \ -b vlm-http-client \ -u http://127.0.0.1:8090 \ --http-timeout 1200 ``` > [!NOTE] > - 注意在执行任意与`vllm`相关命令需追加`--enforce_eager`参数 ## 5. 注意事项 `VastAI`加速卡对`MinerU`的支持情况如下表所示:
使用场景 支持情况
命令行工具(mineru) pipeline 🔴
hybrid-http-client 🔴
hybrid-auto-engine 🔴
vlm-auto-engine 🟢
vlm-http-client 🟢
fastapi服务(mineru-api) pipeline 🔴
hybrid-http-client 🔴
hybrid-auto-engine 🔴
vlm-auto-engine 🟢
vlm-http-client 🟢
gradio界面(mineru-gradio) pipeline 🔴
hybrid-http-client 🔴
hybrid-auto-engine 🔴
vlm-auto-engine 🟢
vlm-http-client 🟢
openai-server服务(mineru-openai-server) 🟢
Tensor并行 (--tensor-parallel-size) 🟢
数据并行 (--data-parallel-size) 🔴
> [!NOTE] > - 🟢: 支持,运行较稳定,精度与NVIDIA GPU基本一致 > - 🟡: 支持但较不稳定,在某些场景下可能出现异常,或精度存在一定差异 > - 🔴: 不支持,无法运行,或精度存在较大差异 > - `vlm-auto-engine`:VastAI仅支持vLLM后端