jeonseonjin
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sample.py
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from transformers import pipeline
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def classify_text(email):
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"""
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Use Facebook BART model to classify an email into "spam" or "not spam"
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Args:
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email (str): The email to classify
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Returns:
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str: The classification of the email ("spam" or "not spam")
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"""
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# Load the BART model for text classification
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classifier = pipeline(task="zero-shot-classification", model="facebook/bart-large-mnli")
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# Classify the email
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labels = ['spam','not spam']
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template = 'This email is {}.'
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result = classifier(email, labels)
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# Get the label with the highest score
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label = result['labels'][0]
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return label
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classify_text('hi I am marketer, we have good product for your good life')
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