Скачать или смотреть Step-by-Step Guide to Installing and Running Datalab’s Chandra OCR on Spheron AI

Chandra is a next-generation OCR model that turns documents into clean, structured Markdown, HTML, or JSON while keeping the layout intact. It handles handwriting, tables, forms, math, diagrams, and multi-language content with high accuracy. It leads the olmOCR benchmark with an 83.1 percent score and outperforms DeepSeek OCR, Mistral OCR API, dots.ocr, and even Google’s GPT-4o.

In this video, I walk you through the full setup on a Spheron AI GPU VM. You deploy your machine, install Python and PyTorch, set up the environment, install Chandra OCR, and launch the Streamlit app. After that, you can upload images or PDFs and get clean structured outputs instantly.

Spheron AI gives you enterprise-grade GPUs in minutes with simple pricing and full control. It makes high-performance OCR workloads fast and affordable.

Full step by step guide with https://www.spheron.ai/
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What you will learn
• How to deploy a GPU VM on Spheron AI
• How to connect through SSH
• How to install Python 3.11 and set up a clean virtual environment
• How to install PyTorch with CUDA
• How to install Chandra OCR and ML libraries
• How to run the Chandra web interface
• How to extract structured Markdown, HTML, and JSON from documents

Chandra turns document understanding into a simple workflow. Spheron AI gives you the hardware speed you need without complexity. This setup lets you process documents with high accuracy and turn them into structured data in seconds.

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