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  ---
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- dataset_info:
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- features:
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- - name: image
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- dtype: image
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- - name: raw_queries
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- list: string
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- - name: broad_topical_query
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- dtype: string
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- - name: broad_topical_explanation
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- dtype: string
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- - name: specific_detail_query
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- dtype: string
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- - name: specific_detail_explanation
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- dtype: string
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- - name: visual_element_query
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- dtype: string
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- - name: visual_element_explanation
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- dtype: string
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- - name: parsed_into_json
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- dtype: bool
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- - name: markdown
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- dtype: string
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- - name: inference_info
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 2485945
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- num_examples: 20
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- download_size: 2340876
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- dataset_size: 2485945
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ tags:
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+ - ocr
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+ - document-processing
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+ - dots-ocr
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+ - multilingual
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+ - markdown
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+ - uv-script
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+ - generated
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+
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+ # Document OCR using dots.ocr
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+
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+ This dataset contains OCR results from images in [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) using DoTS.ocr, a compact 1.7B multilingual model.
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+
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+ ## Processing Details
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+
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+ - **Source Dataset**: [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali)
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+ - **Model**: [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr)
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+ - **Number of Samples**: 20
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+ - **Processing Time**: 2.8 min
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+ - **Processing Date**: 2026-02-25 13:36 UTC
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+
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+ ### Configuration
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+
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+ - **Image Column**: `image`
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+ - **Output Column**: `markdown`
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+ - **Dataset Split**: `train`
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+ - **Batch Size**: 16
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+ - **Prompt Mode**: ocr
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+ - **Max Model Length**: 8,192 tokens
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+ - **Max Output Tokens**: 8,192
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+ - **GPU Memory Utilization**: 80.0%
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+
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+ ## Model Information
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+
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+ DoTS.ocr is a compact multilingual document parsing model that excels at:
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+ - 🌍 **100+ Languages** - Multilingual document support
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+ - 📊 **Table extraction** - Structured data recognition
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+ - 📐 **Formulas** - Mathematical notation preservation
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+ - 📝 **Layout-aware** - Reading order and structure preservation
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+ - 🎯 **Compact** - Only 1.7B parameters
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+
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+ ## Dataset Structure
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+
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+ The dataset contains all original columns plus:
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+ - `markdown`: The extracted text in markdown format
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+ - `inference_info`: JSON list tracking all OCR models applied to this dataset
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+ import json
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+
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+ # Load the dataset
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+ dataset = load_dataset("{output_dataset_id}", split="train")
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+
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+ # Access the markdown text
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+ for example in dataset:
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+ print(example["markdown"])
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+ break
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+
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+ # View all OCR models applied to this dataset
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+ inference_info = json.loads(dataset[0]["inference_info"])
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+ for info in inference_info:
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+ print(f"Column: {info['column_name']} - Model: {info['model_id']}")
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+ ```
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+
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+ ## Reproduction
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+
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+ This dataset was generated using the [uv-scripts/ocr](https://huggingface.co/datasets/uv-scripts/ocr) DoTS OCR script:
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+
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+ ```bash
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+ uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/dots-ocr.py \
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+ davanstrien/ufo-ColPali \
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+ <output-dataset> \
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+ --image-column image \
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+ --batch-size 16 \
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+ --prompt-mode ocr \
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+ --max-model-len 8192 \
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+ --max-tokens 8192 \
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+ --gpu-memory-utilization 0.8
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+ ```
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+
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+ Generated with 🤖 [UV Scripts](https://huggingface.co/uv-scripts)