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README.md

@@ -1,45 +1,101 @@
 ---
-dataset_info:
-  features:
-  - name: document_id
-    dtype: string
-  - name: page_number
-    dtype: int32
-  - name: file_identifier
-    dtype: string
-  - name: image
-    dtype: image
-  - name: text
-    dtype: string
-  - name: alto_xml
-    dtype: string
-  - name: has_image
-    dtype: bool
-  - name: has_alto
-    dtype: bool
-  - name: document_metadata
-    dtype: string
-  - name: has_metadata
-    dtype: bool
-  - name: exam_type
-    dtype: string
-  - name: exam_year
-    dtype: string
-  - name: exam_reference
-    dtype: string
-  - name: markdown
-    dtype: string
-  - name: inference_info
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 13336968
-    num_examples: 100
-  download_size: 9576133
-  dataset_size: 13336968
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+tags:
+- ocr
+- document-processing
+- hunyuan-ocr
+- multilingual
+- markdown
+- uv-script
+- generated
 ---
+
+# Document OCR using HunyuanOCR
+
+This dataset contains OCR results from images in [NationalLibraryOfScotland/Scottish-School-Exam-Papers](https://huggingface.co/datasets/NationalLibraryOfScotland/Scottish-School-Exam-Papers) using HunyuanOCR, a lightweight 1B VLM from Tencent.
+
+## Processing Details
+
+- **Source Dataset**: [NationalLibraryOfScotland/Scottish-School-Exam-Papers](https://huggingface.co/datasets/NationalLibraryOfScotland/Scottish-School-Exam-Papers)
+- **Model**: [tencent/HunyuanOCR](https://huggingface.co/tencent/HunyuanOCR)
+- **Number of Samples**: 100
+- **Processing Time**: 3.6 min
+- **Processing Date**: 2025-11-25 15:51 UTC
+
+### Configuration
+
+- **Image Column**: `image`
+- **Output Column**: `markdown`
+- **Dataset Split**: `train`
+- **Batch Size**: 16
+- **Prompt Mode**: parse-document
+- **Prompt Language**: English
+- **Max Model Length**: 16,384 tokens
+- **Max Output Tokens**: 16,384
+- **GPU Memory Utilization**: 80.0%
+
+## Model Information
+
+HunyuanOCR is a lightweight 1B VLM that excels at:
+- 📝 **Document Parsing** - Full markdown extraction with reading order
+- 📊 **Table Extraction** - HTML format tables
+- 📐 **Formula Recognition** - LaTeX format formulas
+- 📈 **Chart Parsing** - Mermaid/Markdown format
+- 📍 **Text Spotting** - Detection with coordinates
+- 🔍 **Information Extraction** - Key-value, fields, subtitles
+- 🌐 **Translation** - Multilingual photo translation
+
+## Prompt Modes Available
+
+- `parse-document` - Full document parsing (default)
+- `parse-formula` - LaTeX formula extraction
+- `parse-table` - HTML table extraction
+- `parse-chart` - Chart/flowchart parsing
+- `spot` - Text detection with coordinates
+- `extract-key` - Extract specific key value
+- `extract-fields` - Extract multiple fields as JSON
+- `extract-subtitles` - Subtitle extraction
+- `translate` - Document translation
+
+## 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) HunyuanOCR script:
+
+```bash
+uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/hunyuan-ocr.py \
+    NationalLibraryOfScotland/Scottish-School-Exam-Papers \
+    <output-dataset> \
+    --image-column image \
+    --batch-size 16 \
+    --prompt-mode parse-document \
+    --max-model-len 16384 \
+    --max-tokens 16384 \
+    --gpu-memory-utilization 0.8
+```
+
+Generated with [UV Scripts](https://huggingface.co/uv-scripts)