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README.md

+# MedMO
+## 论文
+[MedMO](https://arxiv.org/abs/2602.06965)
+## 模型简介
+MedMO是一个强大的开源多模态基础模型，专为全面的医学图像理解与定位而设计。该模型基于Qwen3-VL架构构建，并在涵盖45个数据集的2600多万个多样化医学样本上进行了训练，在多项医学影像任务中均达到了领先性能水平。MedMO-8B在多样化的医学影像任务（包括视觉问答、问答、报告生成和定位）上的基准性能表现如下：MedMO在各项任务中均取得优于先前模型的一致提升，在MMMU-Med、MedXQA、MMLU-Med、MedQA、MIMIC-CXR上分别提升了1.3%、0.1%、0.7%、24.3%、5.1%，并在细菌分割任务上实现了43.8 IoU的大幅提升。细菌分割IoU指标的显著提升源于细粒度定位监督与高分辨率显微影像数据的引入，这充分彰显了MedMO增强的空间推理与定位能力。
+
+<div align=center>
+    <img src="./doc/perf.jpg"/>
+</div>
+ 
+
+## 环境依赖
+
+|     软件     |                      版本                      |
+| :----------: | :--------------------------------------------: |
+|     DTK      |                    26.04.2                     |
+|    python    |                    3.10.12                     |
+| transformers |                     4.57.6                     |
+|    torch     |   2.5.1+das.opt1.dtk2604.20260116.g78471bfd    |
+|  accelerate  |                     1.12.0                     |
+| torchvision  |   0.20.1+das.opt1.dtk2604.20260116.g65c66897   |
+|  flash_attn  |   2.6.1+das.opt1.dtk2604.20260131.g4edd8bf9    |
+|     vllm     | 0.11.0+das.opt1.rc2.dtk2604.20260128.g0bf89b0c |
+
+推荐使用镜像:harbor.sourcefind.cn:5443/dcu/admin/base/vllm:0.11.0-ubuntu22.04-dtk26.04-0130-py3.10-20260202
+
+- 挂载地址`-v`根据实际模型情况修改
+
+```bash
+docker run -it \
+    --shm-size 60g \
+    --network=host \
+    --name medmo \
+    --privileged \
+    --device=/dev/kfd \
+    --device=/dev/dri \
+    --device=/dev/mkfd \
+    --group-add video \
+    --cap-add=SYS_PTRACE \
+    --security-opt seccomp=unconfined \
+    -u root \
+    -v /opt/hyhal/:/opt/hyhal/:ro \
+    -v /path/your_code_data/:/path/your_code_data/ \
+    harbor.sourcefind.cn:5443/dcu/admin/base/vllm:0.11.0-ubuntu22.04-dtk26.04-0130-py3.10-20260202 bash
+```
+更多镜像可前往[光源](https://sourcefind.cn/#/service-list)下载使用。
+
+关于本项目DCU显卡所需的特殊深度学习库可从[光合](https://developer.sourcefind.cn/tool/)开发者社区下载安装。
+
+
+## 数据集
+
+`暂无`
+
+## 训练
+
+`暂无`
+
+## 推理
+
+## vllm
+
+#### 单机推理
+
+```bash
+## serve启动
+可参考vllm_serve.sh脚本
+vllm serve MBZUAI/MedMO-4B --trust-remote-code --dtype bfloat16 -tp 1 --max-model-len 32768 --port 8010
+## client访问
+可参考vllm_cilent.sh
+curl -X POST "http://localhost:8010/v1/chat/completions"      -H "Content-Type: application/json"     --data '{
+                "model": "MBZUAI/MedMO-4B",
+                "messages": [
+                        {
+                                "role": "user",
+                                "content": "中国的首都是什么"
+                        }
+                ]
+        }'
+
+```
+
+## 效果展示
+
+<div align=center>
+    <img src="./doc/result.png"/>
+</div>
+
+
+### 精度
+
+`DCU与GPU精度一致，推理框架：vllm。`
+
+## 预训练权重
+
+|     **模型名称**     | **权重大小** |  **DCU型号**  | **最低卡数需求** |                         **下载地址**                         |
+| :------------------: | :----------: | :-----------: | :--------------: | :----------------------------------------------------------: |
+| MedMO-4B |     4B      | K100AI |        1         | [MedMO-4B](https://huggingface.co/MBZUAI/MedMO-4B) |
+
+
+
+
+## 源码仓库及问题反馈
+
+- https://developer.sourcefind.cn/codes/modelzoo/medmo_vllm
+## 参考资料
+
+- https://huggingface.co/MBZUAI/MedMO-4B

model.properties

+# 模型唯一标识
+modelCode=2125
+# 模型名称
+modelName=MedMO_vllm
+# 模型描述
+modelDescription=MedMO是一个强大的开源多模态基础模型，专为全面的医学图像理解与定位而设计。
+# 应用场景
+processType=推理
+# 算法类别
+appScenario=多模态
+# 框架类型
+frameType=vllm
+# 加速卡类型
+accelerateType=K100AI

vllm_cilent.sh

+curl -X POST "http://localhost:8010/v1/chat/completions"      -H "Content-Type: application/json"     --data '{
+                "model": "MBZUAI/MedMO-4B",
+                "messages": [
+                        {
+                                "role": "user",
+                                "content": "中国的首都是什么"
+                        }
+                ]
+        }'
\ No newline at end of file

vllm_serve.sh

+vllm serve MBZUAI/MedMO-4B --trust-remote-code --dtype bfloat16 -tp 1 --max-model-len 32768 --port 8010
\ No newline at end of file