Upload README.md with huggingface_hub

README.md

@@ -2,49 +2,49 @@
 tags:
 - ocr
 - document-processing
-- deepseek
-- deepseek-ocr
+- dots-ocr
+- multilingual
 - markdown
 - uv-script
 - generated
 ---
 
-# Document OCR using DeepSeek-OCR
+# Document OCR using dots.ocr
 
-This dataset contains markdown-formatted OCR results from images in [NationalLibraryOfScotland/medical-history-of-british-india](https://huggingface.co/datasets/NationalLibraryOfScotland/medical-history-of-british-india) using DeepSeek-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 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**: [deepseek-ai/DeepSeek-OCR](https://huggingface.co/deepseek-ai/DeepSeek-OCR)
+- **Model**: [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr)
 - **Number of Samples**: 10
-- **Processing Time**: 5.9 min
-- **Processing Date**: 2026-02-14 18:46 UTC
+- **Processing Time**: 6.2 min
+- **Processing Date**: 2026-02-14 18:47 UTC
 
 ### Configuration
 
 - **Image Column**: `image`
 - **Output Column**: `markdown`
 - **Dataset Split**: `train`
-- **Batch Size**: 8
+- **Batch Size**: 16
+- **Prompt Mode**: ocr
 - **Max Model Length**: 8,192 tokens
 - **Max Output Tokens**: 8,192
 - **GPU Memory Utilization**: 80.0%
 
 ## Model Information
 
-DeepSeek-OCR is a state-of-the-art document OCR model that excels at:
-- LaTeX equations - Mathematical formulas preserved in LaTeX format
-- Tables - Extracted and formatted as HTML/markdown
-- Document structure - Headers, lists, and formatting maintained
-- Image grounding - Spatial layout and bounding box information
-- Complex layouts - Multi-column and hierarchical structures
-- Multilingual - Supports multiple languages
+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
 
 The dataset contains all original columns plus:
-- `markdown`: The extracted text in markdown format with preserved structure
+- `markdown`: The extracted text in markdown format
 - `inference_info`: JSON list tracking all OCR models applied to this dataset
 
 ## Usage
@@ -54,7 +54,7 @@ from datasets import load_dataset
 import json
 
 # Load the dataset
-dataset = load_dataset("{{output_dataset_id}}", split="train")
+dataset = load_dataset("{output_dataset_id}", split="train")
 
 # Access the markdown text
 for example in dataset:
@@ -64,23 +64,23 @@ for example in dataset:
 # 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']}}")
+    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) DeepSeek OCR vLLM script:
+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/deepseek-ocr-vllm.py \\
-    NationalLibraryOfScotland/medical-history-of-british-india \\
-    <output-dataset> \\
-    --image-column image
+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 \
+    --prompt-mode ocr \
+    --max-model-len 8192 \
+    --max-tokens 8192 \
+    --gpu-memory-utilization 0.8
 ```
 
-## Performance
-
-- **Processing Speed**: ~0.0 images/second
-- **Processing Method**: Batch processing with vLLM (2-3x speedup over sequential)
-
-Generated with [UV Scripts](https://huggingface.co/uv-scripts)
+Generated with 🤖 [UV Scripts](https://huggingface.co/uv-scripts)