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README.md

@@ -2,62 +2,85 @@
 tags:
 - ocr
 - document-processing
-- glm-ocr
+- deepseek
+- deepseek-ocr
 - markdown
 - uv-script
 - generated
 ---
 
-# Document OCR using GLM-OCR
+# Document OCR 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 GLM-OCR, a compact 0.9B OCR model achieving SOTA performance.
+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.
 
 ## 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**: [deepseek-ai/DeepSeek-OCR](https://huggingface.co/deepseek-ai/DeepSeek-OCR)
 - **Number of Samples**: 10
-- **Processing Time**: 6.2 min
-- **Processing Date**: 2026-02-14 18:31 UTC
+- **Processing Time**: 7.0 min
+- **Processing Date**: 2026-02-14 18:32 UTC
 
 ### Configuration
 
 - **Image Column**: `image`
 - **Output Column**: `markdown`
 - **Dataset Split**: `train`
-- **Batch Size**: 16
+- **Batch Size**: 8
 - **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
+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
 
 ## Dataset Structure
 
 The dataset contains all original columns plus:
-- `markdown`: The extracted text in markdown format
+- `markdown`: The extracted text in markdown format with preserved structure
 - `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) DeepSeek OCR vLLM script:
+
 ```bash
-uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/glm-ocr.py \
-    NationalLibraryOfScotland/medical-history-of-british-india \
-    <output-dataset> \
-    --image-column image \
-    --batch-size 16 \
-    --task ocr
+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
 ```
 
+## 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)