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  #### Model description
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  **Arabic-MARBERT-Sentiment Model** is a Sentiment analysis model that was built by fine-tuning the [MARBERT](https://huggingface.co/UBC-NLP/MARBERT) model. For the fine-tuning, I used [KAUST dataset](https://www.kaggle.com/competitions/arabic-sentiment-analysis-2021-kaust), which includes 3 labels(positive,negative,and neutral).
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  #### How to use
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  To use the model with a transformers pipeline:
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  ```python
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- from transformers import pipeline
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- model = pipeline('text-classification', model='Ammar-alhaj-ali/arabic-MARBERT-sentiment')
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- sentences = ['لقد استمتعت بالحفلة', 'خدمة المطعم كانت محبطة']
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- model(sentences)
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  [{'label': 'positive', 'score': 0.9577557444572449},
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- {'label': 'negative', 'score': 0.9158180952072144}]
 
 
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  #### Model description
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  **Arabic-MARBERT-Sentiment Model** is a Sentiment analysis model that was built by fine-tuning the [MARBERT](https://huggingface.co/UBC-NLP/MARBERT) model. For the fine-tuning, I used [KAUST dataset](https://www.kaggle.com/competitions/arabic-sentiment-analysis-2021-kaust), which includes 3 labels(positive,negative,and neutral).
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  #### How to use
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  To use the model with a transformers pipeline:
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  ```python
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+ >>>from transformers import pipeline
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+ >>>model = pipeline('text-classification', model='Ammar-alhaj-ali/arabic-MARBERT-sentiment')
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+ >>>sentences = ['لقد استمتعت بالحفلة', 'خدمة المطعم كانت محبطة']
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+ >>>model(sentences)
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  [{'label': 'positive', 'score': 0.9577557444572449},
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+ {'label': 'negative', 'score': 0.9158180952072144}]
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+