Datalab To Chandra Deepwiki 🚀 watch the development journey of chandra by datalab to!📝 ocr model that handles complex tables, forms, handwriting with full layout.⭐ 6365 stars | 🍴 683. Chandra ocr 2 is a state of the art ocr model that converts images and pdfs into structured html markdown json while preserving layout information. we have a hosted api for chandra here, which is more accurate and faster. there is a free playground here if you want to try chandra without installing. the easiest way to start is with the cli tools:.
Image Captioning Example Meet chandra, our latest ocr model that tops independent benchmarks and brings powerful new capabilities to document processing. For a comprehensive evaluation across 90 languages (chandra 2 vs gemini 2.5 flash only), see the full 90 language benchmark. we also have a more comprehensive evaluation covering 90 languages, comparing chandra 2 against gemini 2.5 flash. This guide covers all user facing interfaces and features of the chandra ocr system. it provides comprehensive documentation for users who want to process documents into structured formats (markdown, html, json) while preserving layout information. Deepseek ocr did a fine job on clean pages, but it never quite understood the structure. then came chandra ocr, a model that doesn’t just read text but reconstructs the whole idea behind it.
Detailed Benchmarks This guide covers all user facing interfaces and features of the chandra ocr system. it provides comprehensive documentation for users who want to process documents into structured formats (markdown, html, json) while preserving layout information. Deepseek ocr did a fine job on clean pages, but it never quite understood the structure. then came chandra ocr, a model that doesn’t just read text but reconstructs the whole idea behind it. This document provides a high level introduction to the chandra ocr system, including its purpose, architecture, and core components. it serves as an entry point for understanding how the system processes documents into structured output formats. Chandra is an ocr model that outputs markdown, html, and json. it is highly accurate at extracting text from images and pdfs, while preserving layout information. In this guide, we’ve walked through the complete setup and execution of datalab’s chandra ocr, a next generation vision language model for intelligent document understanding. Chandra reads cursive and messy print that trips up traditional ocr. tables — preserves structure including merged cells (colspan rowspan). works on financial filings, invoices, and data tables. math — inline and block equations rendered as latex. handles textbooks, worksheets, and research papers.
Figures And Structured Data This document provides a high level introduction to the chandra ocr system, including its purpose, architecture, and core components. it serves as an entry point for understanding how the system processes documents into structured output formats. Chandra is an ocr model that outputs markdown, html, and json. it is highly accurate at extracting text from images and pdfs, while preserving layout information. In this guide, we’ve walked through the complete setup and execution of datalab’s chandra ocr, a next generation vision language model for intelligent document understanding. Chandra reads cursive and messy print that trips up traditional ocr. tables — preserves structure including merged cells (colspan rowspan). works on financial filings, invoices, and data tables. math — inline and block equations rendered as latex. handles textbooks, worksheets, and research papers.
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