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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 \
<output-dataset> \
--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)
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