OpenBMB发布MiniCPM-OCR 1.0及Jev质检模型
AI 总结
OpenBMB发布两款开源文档OCR模型：1.3B参数的MiniCPM-OCR 1.0用于解析中英文文档，2B参数的MiniCPM-OCR Jev用于为文本、公式和表格的OCR结果评分。OpenBMB称，前者在Real5-OmniDocBench上的得分为93.68，DSpark解码使处理效率提升55%；Jev的AUROC为0.936。代码和模型权重采用Apache 2.0许可发布，报道列出的支持工具包括vLLM、SGLang、llama.cpp和Ollama。
深度见解
Jev还能为其他OCR解析器的输出评分，使现有文档处理流水线无需更换解析器即可增加独立的质检步骤。两个模型参数规模较小，并提供本地部署选项，可能有助于采用这套组合工作流。
| Most OCR models focus on reading documents. MiniCPM-OCR adds a second piece: a model that checks whether the OCR result is actually trustworthy. OpenBMB just released two open-source models: The interesting part is Jev can also evaluate outputs from other OCR systems, so you don't necessarily have to replace your existing pipeline. Both models are open source, with support for vLLM, SGLang, llama.cpp, and Ollama. Hugging Face Links: https://huggingface.co/openbmb/MiniCPM-OCR-Jev https://huggingface.co/openbmb/MiniCPM-OCR-1.0 submitted by /u/Equivalent-Grass-527 [link] [comments] |