Qari OCR 0.3 SNAPSHOT VL 2B Instruct Merged

🚀 Model Card for Model ID

This model is designed for Arabic Optical Character Recognition (OCR), aiming to accurately recognize Arabic text in images, which is of great value for processing Arabic - related visual materials.

🚀 Quick Start

Use the code below to get started with the model. [More Information Needed]

✨ Features

• This is a Vision - Language Model for OCR, specifically tailored for Arabic text recognition.
• It is fine - tuned from the Qwen2 - VL - 2B - Instruct model.

📚 Documentation

Model Details

Model Description

This is the model card of a 🤖 transformers model that has been pushed on the Hub. This model card has been automatically generated.

• Developed by: Ahmed Wasfy, Omer Nacar, Abdelakreem Elkhateb, Mahmoud Reda, Omar Elshehy, Adel Ammar, Wadii Boulila
• Model type: Vision - Language Model for OCR
• Language(s) (NLP): Arabic
• Finetuned from model: Qwen2 - VL - 2B - Instruct

Model Sources

• Paper: QARI - OCR: High - Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation

Uses

Direct Use

This model can be directly used for recognizing Arabic text in images.

Out - of - Scope Use

This model is specifically designed for Arabic text and might not perform well on other languages.

Bias, Risks, and Limitations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

Training Details

Training Data

Trained on specialized synthetic datasets.

Evaluation

The evaluation protocols and results are yet to be fully provided.

Model Examination

Relevant interpretability work for the model is yet to be provided.

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Citation

BibTeX:

@misc{QariOCR2025,
  title={QARI - OCR: High - Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation},
  author={Ahmed Wasfy, Omer Nacar, Abdelakreem Elkhateb, Mahmoud Reda, Omar Elshehy, Adel Ammar, Wadii Boulila},
  year={2025},
  archivePrefix={arXiv},
  url={https://arxiv.org/abs/2506.02295},
  note={Accessed: 2025 - 03 - 03}
}

⚠️ Important Note

This model is specifically designed for Arabic text and might not perform well on other languages.

💡 Usage Tip

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.