Bert Base Arabic Camelbert Mix Did Madar Corpus6

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license:apache-2.0
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CAMeL-Lab
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Quick Summary

CAMeLBERT-Mix DID MADAR Corpus6 Model Model description CAMeLBERT-Mix DID MADAR Corpus6 Model is a dialect identification (DID) model that was built by fine-tuning the CAMeLBERT-Mix model.

Code Examples

How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]
How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]
How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]
How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]
How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]
How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]
How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]
How to usepythontransformers
>>> from transformers import pipeline
>>> did = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar6')
>>> sentences = ['عامل ايه ؟', 'شلونك ؟ شخبارك ؟']
>>> did(sentences)
[{'label': 'CAI', 'score': 0.9996405839920044},
 {'label': 'DOH', 'score': 0.9997853636741638}]

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