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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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- >>> did = pipeline('text-classification', model='Ammar-alhaj-ali/arabic-MARBERT-dialect-identification-city')
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  >>> sentences = ['ناطرين البرنامج', 'اكلنا هوا بهل شروة']
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  >>> model(sentences)
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  [{'label': 'Beirut', 'score': 0.9731963276863098},
 
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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-dialect-identification-city')
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  >>> sentences = ['ناطرين البرنامج', 'اكلنا هوا بهل شروة']
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  >>> model(sentences)
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  [{'label': 'Beirut', 'score': 0.9731963276863098},