OpenBMB· @OpenBMB · X·· 4 小时前AI 评分50
AI 导读
OpenBMB 开源 MiniCPM-OCR 系列模型，把文档解析与 OCR 结果可靠性评估配套提供。MiniCPM-OCR 1.0 是 1.3B 参数的中英文文档解析模型，支持扫描页、拍照文档、倾斜和弯曲页面，可处理表格、公式、PDF 和关键信息抽取，并支持查看 Markdown 源码与预览解析结果；MiniCPM-OCR Jev 是独立模型，用于评估 OCR 结果可靠性，帮助识别需要人工复核的输出。模型权重开放在 GitHub 和 Hugging Face，支持多种部署方式。
正文 · 原文
📄 Parsing documents is only half the job. Knowing which outputs need a second look matters too. 🔍
MiniCPM-OCR pairs document parsing with OCR reliability assessment to help build more dependable workflows. Thanks @dravenip for the thoughtful overview! 🚀
DOCUMENT PARSING IS GETTING REALLY INTERESTING MiniCPM-OCR is an open-source model family from @OpenBMB and ModelBest built to turn documents into structured, usable information. → MiniCPM-OCR 1.0 is a compact 1.3B-parameter model for English and Chinese documents → handles scanned pages, photographed documents, tilted inputs and even curved pages → supports tables, formulas, PDFs and key information extraction → lets you inspect the Markdown source and preview the parsed output the family also includes MiniCPM-OCR Jev, a separate model that assesses the reliability of OCR results and helps identify outputs that may need human review. pretty cool to see document parsing and output assessment tackled together, with open-source weights and multiple deployment options. GitHub: http://github.com/OpenBMB/MiniCPM-OCR Hugging Face: MiniCPM-OCR 1.0：http://huggingface.co/openbmb/MiniCPM-OCR-1.0 MiniCPM-OCR Jev：http://huggingface.co/openbmb/MiniCPM-OCR-Jev在 X 查看被引用的帖子
来源：OpenBMB · x.com