💜 Github      🤗 Hugging Face      📚 Cookbooks    🖥️ Demo    🕌 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. Outperforms Google Vision and Teseract in the Arabic context. This model is the highest performing open source Arabic model ever for handwriting and manuscripts, trained on 65,747 diverse samples, including: Printed texts (from sources such as a font) Handwriting (from a font collection) Historical manuscripts (rare archival documents) 📊 Performance 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 💡 Unique Features ✅ Supports full text (not isolated characters) ✅ Handles old manuscripts (even low quality) ✅ No complex preprocessing required ✅ Fully open source customizable ✅ Supports full linguistic context for compr…
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