Model Card for Model ID
This model is designed for Arabic Optical Character Recognition (OCR).
Model Details
Model Description
This is the model card of a π€ 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
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- Model type: Vision-Language Model for OCR
- Language(s) (NLP): Arabic
- License: [More Information Needed]
- Finetuned from model [optional]: Qwen2-VL-2B-Instruct
Model Sources [optional]
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- Paper: QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation
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Uses
Direct Use
This model can be directly used for recognizing Arabic text in images.
Downstream Use [optional]
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Out-of-Scope Use
This model is specifically designed for Arabic text and might not perform well on other languages.
Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
Trained on specialized synthetic datasets.
Training Procedure
Preprocessing [optional]
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Training Hyperparameters
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Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Summary
Model Examination [optional]
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation [optional]
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}
}
APA:
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Glossary [optional]
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