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Datalab

datalab-to

SoTA models to make your documents machine-readable

Models in Library4
Datasets in Library0
Models on Hugging Face15
Followers552

Models

Model · Image and text to text

chandra-ocr-2

Datalab

Chandra 2 is a state of the art OCR model from Datalab that outputs markdown, HTML, and JSON. It is highly accurate at extracting text from images and PDFs, while preserving layout information. Try Chandra in the free playground, or use the hosted API for higher accuracy and speed. - 85.8% olmocr bench score (sota), 77.8% multilingual bench score (12% improvement over Chandra 1) - Significant improvements to math, tables, complex layouts - 90+ language support with major accuracy gains - Convert documents to markdown, HTML, or JSON with detailed layout information - Reconstructs forms accurately, including checkboxes - Strong performance with tables, math, and complex layouts - Extracts…

Open weights openrail 5.3B parameters 262,144 tokens transformers

Model · Image and text to text

surya-ocr-2

Datalab

Surya is a 650M param OCR model with these features: - Accuracy - scores 83.3% on olmOCR-bench (top under 3B params) - Multilingual - scores 87.2% on an internal benchmark set of 91 languages (more here) - Layout analysis (table, image, header, etc.) with reading order - Table recognition (rows + columns) It works on a range of documents (see usage and benchmarks). Our managed platform runs both Surya, and variants of our highest accuracy model, Chandra. Get started with $5 in free credits — sign up (takes under 30 seconds) or try our free public playground. Surya is named for the Hindu sun god, who has universal vision. The Surya code is licensed under Apache 2.0. The model weights use a…

Open weights openrail 686M parameters 262,144 tokens transformers

Model · Image and text to text

surya-ocr-2-gguf

Datalab

Surya is a 650M param OCR model with these features: - Accuracy - scores 83.3% on olmOCR-bench (top under 3B params) - Multilingual - scores 87.2% on an internal benchmark set of 91 languages (more here) - Layout analysis (table, image, header, etc.) with reading order - Table recognition (rows + columns) It works on a range of documents (see usage and benchmarks). Our managed platform runs both Surya, and variants of our highest accuracy model, Chandra. Get started with $5 in free credits — sign up (takes under 30 seconds) or try our free public playground. Surya is named for the Hindu sun god, who has universal vision. The Surya code is licensed under Apache 2.0. The model weights use a…

Open weights openrail 262,144 tokens transformers

Model · Object detection

surya_layout2

Datalab

A lightweight document layout detection model used by Surya. It detects layout regions (text, tables, figures, headers, captions, equations, etc.) on a page image and runs on CPU or GPU. This is the "fast" layout detector — a compact object detector that serves as a drop-in alternative to Surya's VLM-based layout model. Documentation, installation, and everything else lives in the Point the fast layout predictor at this checkpoint: Or make it the default so the CLI and library use it without an explicit path: Released under the AI Pubs OpenRAIL-M license (see LICENSE) — the same license as the surya-ocr-2 model weights.

Open weights openrail surya