Model overview
- QARI-OCR v0.3 is a specialized vision-language model fine-tuned for Arabic Optical Character Recognition with a focus on **structural document understanding**. - Built on Qwen2-VL-2B-Instruct, this model excels at preserving document layouts, HTML tags, and formatting while transcribing Arabic text. - It is described in detail in the paper QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation. - 📐 **Layout-Aware Recognition**: Preserves document structure with HTML/Markdown tags - 🔤 **Full Diacritics Support**: Accurate recognition of tashkeel (Arabic diacritical marks) - 📝 **Multi-Font Handling**: Trained on 12 diverse Arabic fonts (14px-100px) - 🎯 **Structure-First Design**: Optimized for documents with headers, body text, and complex layouts - ⚡ **Efficient Training**: Only 11 hours on single GPU with 10k samples - 🖼️ **Robust Performance**: Handles low-resolution and degraded images While QARI v0.2 achieves better raw text accuracy (CER: 0.061), QARI v0.3 excels in: - ✅ **HTML/Markdown structure preservation** - ✅ **Document layout understanding** - ✅ **Handwritten text recognition** (initial capabilities) - ✅ **5x faster training** than v0.2
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
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Estimate monthly base token costs
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Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
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Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。