1 link tagged with all of: chandra ocr 2 + benchmarks + document processing + datalab + multimodal
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Chandra OCR 2 is Datalab's optical character recognition model that converts documents to markdown, HTML, or JSON while preserving layout. It scores 85.8% on the olmOCR benchmark and supports 90+ languages with strong performance on tables, math, handwriting, and complex layouts.
- Chandra 2 achieves 85.8% on olmOCR benchmark (state-of-art), a 12% improvement over Chandra 1's 77.8% multilingual score, with particular strength in math, tables, and complex layouts
- Available through multiple deployment methods: HuggingFace Transformers, vLLM, SGLang, and Docker, with quickstart CLI tools for local use
- Handles 90+ languages, extracts images with captions, reconstructs forms accurately including checkboxes, and supports handwriting recognition across diverse document types