OpenBMB/MiniCPM-OCR

选用指南

AI 根据 README 整理 · 2026/10/28 13:51:50

使用方式

可通过API调用，或在本地部署模型将PDF和图片解析为Markdown或JSON，使用Jev模型对结果评分。

查看 README 依据

```text Read and execute https://github.com/OpenBMB/MiniCPM-OCR/blob/main/docs/SKILL_en.md ``` If you have already cloned this repository, you can use `./docs/SKILL_en.md` directly. ### API Use the API to access MiniCPM-OCR 1.0 recognition and MiniCPM-OCR Jev quality scoring. [MiniCPM-OCR 1.0 API example](./docs/minicpm_ocr_api_en.md) &emsp;·&emsp; [MiniCPM-OCR Jev API example](./docs/minicpm_ocr_jev_api_en.md) (coming soon) <a id="手动部署"></a> <a id="本地部署"></a> ### Local Deployment

Run the models on your own hardware: MiniCPM-OCR 1.0 parses PDFs and images into Markdown or JSON, while MiniCPM-OCR Jev scores the parsing results. [MiniCPM-OCR 1.0 deployment tutorial](./docs/minicpmvocr_tutorial_en.md) · [MiniCPM-OCR Jev deployment tutorial](./docs/minicpm_ocr_jev_tutorial_en.md) <a id="模型微调"></a> ### Fine-Tuning | Model | Fine-tuning tutorial | | :--- | :--- | | MiniCPM-OCR 1.0 | [LLaMA-Factory](./docs/llamafactory_minicpm_ocr_french_en.md) · [Swift](./docs/swift_minicpm_ocr_french_en.md) | | MiniCPM-OCR Jev | [Swift](./docs/finetune_jev_en.md) |

部署要求

支持vLLM、SGLang、llama.cpp和Ollama等推理框架，并提供BF16、GGUF等量化版本，需要相应的硬件环境。

查看 README 依据

- 🛠️ **Easy deployment and development**: MiniCPM-OCR 1.0 supports **vLLM, SGLang, llama.cpp, and Ollama from day one**, with multiple chip platforms and quantized versions available at release. It **supports further fine-tuning** and provides a **[pip SDK](#local-deployment)** and a **[full-featured API](#api)** for application integration and customization. You can also **[get started quickly with SKILL.md](#skill)**. Try the Online Demo ([CN](https://platform.modelbest.cn/console/playground/document-parse) / [Global](https://platform.modelbest.ai/console/playground/document-parse)) to