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---
tags:
- ocr
- document-processing
- dots-ocr
- multilingual
- markdown
- uv-script
- generated
---
# Document OCR using dots.ocr
This dataset contains OCR results from images in [davanstrien/transcribed-slates](https://huggingface.co/datasets/davanstrien/transcribed-slates) using DoTS.ocr, a compact 1.7B multilingual model.
## Processing Details
- **Source Dataset**: [davanstrien/transcribed-slates](https://huggingface.co/datasets/davanstrien/transcribed-slates)
- **Model**: [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr)
- **Number of Samples**: 100
- **Processing Time**: 1.5 min
- **Processing Date**: 2025-10-22 15:19 UTC
### Configuration
- **Image Column**: `image`
- **Output Column**: `markdown`
- **Dataset Split**: `train`
- **Batch Size**: 256
- **Prompt Mode**: ocr
- **Max Model Length**: 8,192 tokens
- **Max Output Tokens**: 8,192
- **GPU Memory Utilization**: 80.0%
## Model Information
DoTS.ocr is a compact 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
- 🎯 **Compact** - Only 1.7B parameters
## 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 OCR script:
```bash
uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/dots-ocr.py \
davanstrien/transcribed-slates \
<output-dataset> \
--image-column image \
--batch-size 256 \
--prompt-mode ocr \
--max-model-len 8192 \
--max-tokens 8192 \
--gpu-memory-utilization 0.8
```
Generated with 🤖 [UV Scripts](https://huggingface.co/uv-scripts)
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