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Arabart
A
Arabart
Developed by moussaKam
AraBART is the first Arabic encoder-decoder model based on the BART architecture with end-to-end pretraining, demonstrating optimal performance across multiple abstractive summarization datasets.
Downloads 857
Release Time : 3/9/2022
Model Overview
AraBART is an Arabic language model based on the BART architecture, primarily used for text generation and summarization tasks, supporting Arabic language processing.
Model Features
First Arabic BART Model
The first Arabic encoder-decoder model based on the BART architecture with end-to-end pretraining.
High-Performance Summarization
Demonstrates optimal performance across multiple abstractive summarization datasets, surpassing other baseline models.
Lightweight Architecture
Utilizes the BART-Base architecture with a moderate parameter count (139 million), suitable for various application scenarios.
Model Capabilities
Arabic Text Generation
Arabic Summarization
Text Infilling
Use Cases
Text Processing
News Summarization
Automatically generates concise summaries of Arabic news articles.
Outperforms other Arabic language models in test datasets.
Text Infilling
Automatically completes missing parts of Arabic text based on context.
Accurately understands context and generates reasonable completions.
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