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README.md

@@ -2,24 +2,24 @@
 tags:
 - ocr
 - document-processing
-- glm-ocr
+- dots-ocr
+- multilingual
 - markdown
 - uv-script
 - generated
 ---
 
-# Document OCR using GLM-OCR
+# Document OCR using dots.ocr
 
-This dataset contains OCR results from images in [NationalLibraryOfScotland/medical-history-of-british-india](https://huggingface.co/datasets/NationalLibraryOfScotland/medical-history-of-british-india) using GLM-OCR, a compact 0.9B OCR model achieving SOTA performance.
+This dataset contains OCR results from images in [NationalLibraryOfScotland/medical-history-of-british-india](https://huggingface.co/datasets/NationalLibraryOfScotland/medical-history-of-british-india) using DoTS.ocr, a compact 1.7B multilingual model.
 
 ## Processing Details
 
 - **Source Dataset**: [NationalLibraryOfScotland/medical-history-of-british-india](https://huggingface.co/datasets/NationalLibraryOfScotland/medical-history-of-british-india)
-- **Model**: [zai-org/GLM-OCR](https://huggingface.co/zai-org/GLM-OCR)
-- **Task**: text recognition
+- **Model**: [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr)
 - **Number of Samples**: 50
-- **Processing Time**: 8.9 min
-- **Processing Date**: 2026-02-14 19:13 UTC
+- **Processing Time**: 10.2 min
+- **Processing Date**: 2026-02-14 19:16 UTC
 
 ### Configuration
 
@@ -27,21 +27,19 @@ This dataset contains OCR results from images in [NationalLibraryOfScotland/medi
 - **Output Column**: `markdown`
 - **Dataset Split**: `train`
 - **Batch Size**: 16
+- **Prompt Mode**: ocr
 - **Max Model Length**: 8,192 tokens
 - **Max Output Tokens**: 8,192
-- **Temperature**: 0.01
-- **Top P**: 1e-05
 - **GPU Memory Utilization**: 80.0%
 
 ## Model Information
 
-GLM-OCR is a compact, high-performance OCR model:
-- 0.9B parameters
-- 94.62% on OmniDocBench V1.5
-- CogViT visual encoder + GLM-0.5B language decoder
-- Multi-Token Prediction (MTP) loss for efficiency
-- Multilingual: zh, en, fr, es, ru, de, ja, ko
-- MIT licensed
+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
 
@@ -49,15 +47,40 @@ 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/glm-ocr.py \
+uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/dots-ocr.py \
     NationalLibraryOfScotland/medical-history-of-british-india \
     <output-dataset> \
     --image-column image \
     --batch-size 16 \
-    --task ocr
+    --prompt-mode ocr \
+    --max-model-len 8192 \
+    --max-tokens 8192 \
+    --gpu-memory-utilization 0.8
 ```
 
-Generated with [UV Scripts](https://huggingface.co/uv-scripts)
+Generated with 🤖 [UV Scripts](https://huggingface.co/uv-scripts)