- Add rolm-ocr.py: Fast general-purpose OCR using reducto/RolmOCR
- Add inference_info tracking to all OCR scripts for multi-model comparison
- Add --shuffle and --seed flags for random sampling
- Add automatic dataset card generation with processing details
- Update README.md with new script documentation and feature descriptions
- Dynamic column naming for RolmOCR (e.g., rolmocr_text)
These enhancements support iterative model comparison workflows and better sampling strategies for OCR evaluation.
Optimize default settings based on performance testing
- Increase default batch size from 8 to 32
- Increase default GPU memory utilization from 0.7 to 0.8
- Update README with new defaults and simple performance tip
- These changes provide ~2-3x speedup based on testing
- UV script for document OCR using Nanonets-OCR-s model
- Features: LaTeX equations, tables, document structure
- Supports batch processing with vLLM
- Includes HF Jobs examples for running on cloud
- Added proper CUDA checks and error handling
