Upload README.md with huggingface_hub

README.md

@@ -1,37 +1,88 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: raw_queries
-    list: string
-  - name: broad_topical_query
-    dtype: string
-  - name: broad_topical_explanation
-    dtype: string
-  - name: specific_detail_query
-    dtype: string
-  - name: specific_detail_explanation
-    dtype: string
-  - name: visual_element_query
-    dtype: string
-  - name: visual_element_explanation
-    dtype: string
-  - name: parsed_into_json
-    dtype: bool
-  - name: markdown
-    dtype: string
-  - name: inference_info
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 312424
-    num_examples: 3
-  download_size: 330840
-  dataset_size: 312424
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+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)