sinhala-deepseek-ocr-Qlora

Sinhala DeepSeek-OCR LoRA Model 🇱🇰

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Fine-tuned DeepSeek-OCR model for high-accuracy Sinhala language OCR on historical legal documents

Quick Start • Performance • Usage • Training • 🎓 Citation

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Model Description

This model is a LoRA fine-tuned version of DeepSeek-OCR specifically optimized for Sinhala (සිංහල) language OCR on historical and contemporary legal documents. The model achieves 98% character accuracy on a test set spanning over a century of Sri Lankan legal texts (1910-2024).

Key Features

• High Accuracy: above 90.0% character accuracy on Sinhala legal documents
• Historical Coverage: Trained on documents from 1910-2024
• Efficient: LoRA fine-tuning allows 4-bit quantization with minimal quality loss
• Production Ready: Optimized for inference with Unsloth framework
• Low Resource: Runs on consumer GPUs with 4-bit quantization (~6GB VRAM)

Model Details

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Performance Metrics

Overall Performance

Accuracy Distribution

Baseline Comparison

## 🎓 Citation

If you use this model, dataset, or research in your work, please cite our paper:

```bibtex
@misc{dilhara2026crosstemporalsinhalaocrpagelevel,
      title={Cross-Temporal Sinhala OCR: Page-Level Adaptation and Diachronic Analysis}, 
      author={Avisha Dilhara and Nevidu Jayatilleke},
      year={2026},
      eprint={2606.29378},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={[https://arxiv.org/abs/2606.29378](https://arxiv.org/abs/2606.29378)}
}