Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2

🥇 The first open-source Arabic model to achieve 97.2% accuracy in extracting Arabic text from historical books and manuscripts. This model is the highest-performing open-source Arabic model ever for handwriting and manuscripts, trained on 65,747 diverse samples, including: Scale Value Explanation Evaluation Loss 0.6564, the lowest globally in Arabic OCR Character Error Rate (CER) 4.51%, excellent (less than 5% = high quality) Word Error Rate (WER) ~9%, very good for handwritten texts Estimated Accuracy 97.2%, outperforms commercial models Average Time 0.30-second inference, fast for live applications

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