--- tags: - ocr - document-processing - dots-mocr - multilingual - markdown - uv-script - generated --- # Document OCR using dots.mocr This dataset contains OCR results from images in [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) using dots.mocr, a 3B multilingual model with SOTA document parsing and SVG generation. ## Processing Details - **Source Dataset**: [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) - **Model**: [rednote-hilab/dots.mocr](https://huggingface.co/rednote-hilab/dots.mocr) - **Number of Samples**: 3 - **Processing Time**: 2.0 min - **Processing Date**: 2026-03-19 17:38 UTC ### Configuration - **Image Column**: `image` - **Output Column**: `markdown` - **Dataset Split**: `train` - **Batch Size**: 16 - **Prompt Mode**: ocr - **Max Model Length**: 24,000 tokens - **Max Output Tokens**: 24,000 - **GPU Memory Utilization**: 90.0% ## Model Information dots.mocr is a 3B multilingual document parsing model that excels at: - 100+ Languages — Multilingual document support - Table extraction — Structured data recognition - Formulas — Mathematical notation preservation - Layout-aware — Reading order and structure preservation - Web screen parsing — Webpage layout analysis - Scene text spotting — Text detection in natural scenes - SVG code generation — Charts, UI layouts, scientific figures to SVG ## Dataset Structure The dataset contains all original columns plus: - `markdown`: The extracted text in markdown format - `inference_info`: JSON list tracking all OCR models applied to this dataset ## Usage ```python from datasets import load_dataset import json # Load the dataset dataset = load_dataset("{output_dataset_id}", split="train") # Access the markdown text for example in dataset: print(example["markdown"]) break # View all OCR models applied to this dataset inference_info = json.loads(dataset[0]["inference_info"]) for info in inference_info: print(f"Column: {info['column_name']} - Model: {info['model_id']}") ``` ## Reproduction This dataset was generated using the [uv-scripts/ocr](https://huggingface.co/datasets/uv-scripts/ocr) dots.mocr script: ```bash uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/dots-mocr.py \ davanstrien/ufo-ColPali \ \ --image-column image \ --batch-size 16 \ --prompt-mode ocr \ --max-model-len 24000 \ --max-tokens 24000 \ --gpu-memory-utilization 0.9 ``` Generated with [UV Scripts](https://huggingface.co/uv-scripts)