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README.md

+# Nanonets-OCR-s
+## 论文
+暂无
+
+## 模型简介
+
+Nanonets-OCR-s是由Nanonets推出的一款强大且先进的图像转Markdown光学字符识别（OCR）模型。它远不止于传统的文本提取，更能将文档转换为带有智能内容识别和语义标记的结构化Markdown格式，使其成为大型语言模型（LLM）下游处理的理想选择。
+
+Nanonets-OCR-s集成了众多功能，旨在轻松处理复杂文档：
+
+- LaTeX 公式识别：自动将数学方程式和公式转换为格式正确的 LaTeX 语法。它能区分行内公式（...）和独立成行的公式（...）。  
+- 智能图像描述：使用结构化的  标签描述文档中的图像，使其易于被大型语言模型（LLM）处理。它可以描述包括徽标、图表、图形等各种图像类型，并详述其内容、风格和上下文。  
+- 签名检测与隔离：识别并将签名与其他文本隔离开来，将其输出在  标签内。这对于处理法律和商业文件至关重要。  
+- 水印提取：检测并提取文档中的水印文本，并将其置于  标签内。  
+- 智能复选框处理：将表单中的复选框和单选按钮转换为标准化的 Unicode 符号（☐, ☑, ☒），以确保处理的一致性和可靠性。  
+- 复杂表格提取：准确地从文档中提取复杂表格，并将其转换为 Markdown 和 HTML 两种表格格式。
+
+## 环境依赖
+| 软件 | 版本 |
+| :------: | :------: |
+| DTK | 26.04 |
+| python | 3.10.12 |
+| torch | 2.9.0+das.opt1.dtk2604.20260206.g275d08c2 |
+| transformers | 5.0.0.dev0 |
+| vllm | 0.15.1+das.opt1.alpha.dtk2604.20260220.g2799735a |
+
+推荐使用镜像: harbor.sourcefind.cn:5443/dcu/admin/base/custom:vllm0.15.1-ubuntu22.04-dtk26.04-0130-py3.10-20260220
+
+- 挂载地址`-v`根据实际模型情况修改
+
+```bash
+docker run -it \
+    --shm-size 200g \
+    --network=host \
+    --name Nanonets-OCR-s \
+    --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/custom:vllm0.15.1-ubuntu22.04-dtk26.04-0130-py3.10-20260220 bash
+```
+
+更多镜像可前往[光源](https://sourcefind.cn/#/service-list)下载使用，其它包安装：
+```
+pip install pycountry
+```
+
+## 数据集
+`暂无`
+
+## 训练
+`暂无`
+
+## 推理
+### vllm
+#### 单机推理
+```bash
+## serve启动
+vllm serve  nanonets/Nanonets-OCR-s    --trust-remote-code --dtype bfloat16 -tp 1  --port 8010
+
+## client访问
+curl -X POST "http://localhost:8010/v1/chat/completions" \
+	-H "Content-Type: application/json" \
+	--data '{
+		"model": "nanonets/Nanonets-OCR-s",
+		"messages": [
+			{
+				"role": "user",
+				"content": [
+					{
+						"type": "text",
+						"text": "Describe this image in one sentence."
+					},
+					{
+						"type": "image_url",
+						"image_url": {
+							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
+						}
+					}
+				]
+			}
+		]
+	}'
+
+```
+
+## 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|
+|:-----:|:----------:|:----------:|:---------------------:|:----------:|
+| Nanonets-OCR-s | 4B | BW1000 | 1 | [Modelscope](https://huggingface.co/nanonets/Nanonets-OCR-s) |
+
+
+## 源码仓库及问题反馈
+- https://developer.sourcefind.cn/codes/modelzoo/nanonets-ocr-s_vllm
+
+## 参考资料
+- https://github.com/NanoNets/docext/tree/dev/markdown
\ No newline at end of file

model.properties

+# 模型唯一标识
+modelCode=2250
+# 模型名称
+modelName=Nanonets-OCR-s_vllm
+# 模型描述
+modelDescription=Nanonets-OCR-s是由Nanonets推出的一款强大且先进的图像转Markdown光学字符识别（OCR）模型。
+# 运行过程
+processType=推理
+# 算法类别
+appCategory=OCR
+# 框架类型
+frameType=vllm
+# 加速卡类型
+accelerateType=BW1000