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README.md

@@ -2,54 +2,90 @@
 tags:
 - ocr
 - document-processing
-- unlimited-ocr
-- baidu
+- olmocr
 - markdown
 - uv-script
 - generated
 ---
 
-# Document OCR using Unlimited-OCR
+# Document OCR using olmOCR-2-7B-1025-FP8
 
-This dataset contains OCR results for [davanstrien/encyclopaedia-britannica-1771](https://huggingface.co/datasets/davanstrien/encyclopaedia-britannica-1771)
-produced by [baidu/Unlimited-OCR](https://huggingface.co/baidu/Unlimited-OCR) with vLLM.
+This dataset contains markdown-formatted OCR results from images in [davanstrien/encyclopaedia-britannica-1771](https://huggingface.co/datasets/davanstrien/encyclopaedia-britannica-1771) using olmOCR-2-7B.
 
 ## Processing Details
 
 - **Source Dataset**: [davanstrien/encyclopaedia-britannica-1771](https://huggingface.co/datasets/davanstrien/encyclopaedia-britannica-1771)
-- **Model**: [baidu/Unlimited-OCR](https://huggingface.co/baidu/Unlimited-OCR)
+- **Model**: [allenai/olmOCR-2-7B-1025-FP8](https://huggingface.co/allenai/olmOCR-2-7B-1025-FP8)
 - **Number of Samples**: 5
-- **Processing Time**: 2.3 min
-- **Processing Date**: 2026-07-07 23:47 UTC
+- **Processing Time**: 0h 3m 18s
+- **Processing Date**: 2026-07-08 06:41 UTC
+
+### Configuration
+
+- **Image Column**: `image`
 - **Output Column**: `markdown`
-- **Split**: `train`
+- **Dataset Split**: `train`
+- **Batch Size**: 16
+- **Max Model Length**: 16,384 tokens
+- **Max Output Tokens**: 8,192
+- **GPU Memory Utilization**: 80.0%
 
-## Output
+## Model Information
 
-Grounding markup was stripped (`--strip-grounding`); the column holds clean text.
+olmOCR-2-7B is a high-quality document OCR model based on Qwen2.5-VL-7B-Instruct, fine-tuned on olmOCR-mix-1025 dataset and optimized with GRPO reinforcement learning.
 
-Tables are returned as HTML and equations as LaTeX.
+Key features:
+- 📐 **LaTeX equations** - Mathematical formulas in LaTeX format
+- 📊 **HTML tables** - Structured table extraction
+- 📝 **Document structure** - Headers, lists, formatting preserved
+- 🖼️ **Figure descriptions** - Charts and figures labeled with descriptions
+- 🔄 **Rotation detection** - Metadata about document orientation
+- 📑 **Natural reading order** - Handles multi-column and complex layouts
+- 🎯 **High accuracy** - Scores 82.4 ± 1.1 on olmOCR-Bench
 
-## Usage
+## Output Format
 
-```python
-from datasets import load_dataset
+Each row contains:
+- Original image from source dataset
+- `markdown`: Extracted document content in markdown format
+- `olmocr_metadata`: JSON with document metadata (language, rotation, table/diagram flags)
 
-ds = load_dataset("davanstrien/ocr-bench-smoke", split="train")
-print(ds[0]["markdown"])
-```
+## Columns
 
-## Reproduction
+- `image`: Original document image
+- `markdown`: Extracted text and structure in markdown
+- `olmocr_metadata`: Document metadata (primary_language, is_rotation_valid, rotation_correction, is_table, is_diagram)
+- `inference_info`: Processing metadata (model, script version, timestamp)
 
-Generated with the [uv-scripts/ocr](https://huggingface.co/datasets/uv-scripts/ocr) Unlimited-OCR
-vLLM recipe. Unlimited-OCR needs Baidu's dedicated vLLM image:
+## Reproduction
 
 ```bash
-hf jobs uv run --flavor l4x1 -s HF_TOKEN \
-    --image vllm/vllm-openai:unlimited-ocr --python /usr/bin/python3 \
-    -e PYTHONPATH=/usr/local/lib/python3.12/dist-packages \
-    https://huggingface.co/datasets/uv-scripts/ocr/raw/main/unlimited-ocr-vllm.py \
-    davanstrien/encyclopaedia-britannica-1771 <output-dataset>
+# Using HF Jobs (recommended)
+hf jobs uv run --flavor l4x1 \
+  -s HF_TOKEN \
+  https://huggingface.co/datasets/uv-scripts/ocr/raw/main/olmocr2-vllm.py \
+  davanstrien/encyclopaedia-britannica-1771 \
+  your-username/output-dataset
+
+# Local with GPU
+uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/olmocr2-vllm.py \
+  davanstrien/encyclopaedia-britannica-1771 \
+  your-username/output-dataset
 ```
 
-Generated with [UV Scripts](https://huggingface.co/uv-scripts)
+## Citation
+
+```bibtex
+@misc{olmocr,
+      title={{olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models}},
+      author={Jake Poznanski and Jon Borchardt and Jason Dunkelberger and Regan Huff and Daniel Lin and Aman Rangapur and Christopher Wilhelm and Kyle Lo and Luca Soldaini},
+      year={2025},
+      eprint={2502.18443},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2502.18443},
+}
+```
+
+---
+*Generated with [uv-scripts/ocr](https://huggingface.co/datasets/uv-scripts/ocr)*