MinerU2.5 is a compact 1.2B VLM with a smart two-stage, coarse-to-fine pipeline (global layout → native-res crops) that delivers state-of-the-art doc parsing with low compute.
MinerU2.5 正式发布 🎉，这个参数规模仅 1.2B 的视觉-语言模型，通过创新的解耦架构和数据引擎，实现 SOTA 准确率，同时显著降低计算开销！！团队也公布了技术报告，一起看看它的模型组成、训练细节和实战表现 👇 1. 背景与挑战…
testing MineU, 1.2B VLM for 'efficient' document parsing. its not heavy, im really optimistic. huggingface.co/opendatalab/Mi…
MinerU是上海AI 实验室的哦，如果觉得vlm慢，可以使用Sglang加速，快到起飞。当然，这对设备有一定性能要求和门槛
#MathFusion is a novel framework that enhances mathematical reasoning through cross-problem instruction synthesis. 🦾Experimental results demonstrate that it achieves substantial improvements in mathematical reasoning while maintaining high data efficiency. #AI #Datasets
Vis3 is a visualization tool for #LLM and machine learning data, supporting cloud storage platforms with S3 protocol and various data formats. It offers interactive visualization through JSON, HTML, Markdown, and image views for efficient #data analysis.
#MinerU has officially cooperated with @CherryStudioHQ. You can directly call the MinerU function in Cherry Studio. MinerU officially provides each Cherry Studio user with a document processing quota of up to 500 pages per day.
#LabelLLM introduces an open-source platform dedicated to optimizing the #data annotation process integral to the development of #LLM. There are key features of LabelLLM. Try me👉 labelu-llm-demo.shlab.tech/supplier/task
#MinerU leverages the sophisticated PDF-Extract-Kit models to extract content from diverse documents effectively and ensure the accuracy of the final results. As its core, MinerU commits to facilitating the #mathematical and extended formulas parsing.
Agentic Document Extraction just got much faster! From previous 135sec median processing time down to 8sec. Extracts not just text but diagrams, charts, and form fields from PDFs to give LLM-ready output. Please see the video for details and some application ideas.
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