面壁智能 OpenBMB 推出 MiniCPM-OCR 模型家族，含解析与可靠性评估两个模型

文档解析正变得非常有趣 MiniCPM-OCR 是来自 @OpenBMB 和 ModelBest 的开源模型家族，旨在将文档转化为结构化、可用的信息。 → MiniCPM-OCR 1.0 是一个紧凑的 1.3B 参数模型，适用于中英文文档 → 可处理扫描页、拍照文档、倾斜输入甚至弯曲页面 → 支持表格、公式、PDF 和关键信息抽取 → 可查看 Markdown 源码并预览解析输出 该家族还包括 MiniCPM-OCR Jev，这是一个独立模型，用于评估 OCR 结果的可靠性，并帮助识别可能需要人工复核的输出。 看到文档解析和输出评估被一起解决，并且提供开源权重和多种部署方式，这相当酷。 GitHub：https://t.co/7SPyXoTA2o Hugging Face： MiniCPM-OCR 1.0：https://t.co/07gayee7eY MiniCPM-OCR Jev：https://t.co/jn6LLkFNft

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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: https://t.co/7SPyXoTA2o Hugging Face: MiniCPM-OCR 1.0：https://t.co/07gayee7eY MiniCPM-OCR Jev：https://t.co/jn6LLkFNft