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import sys |
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from transformers import pipeline |
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candidate_labels_spam = ['Spam', 'not Spam'] |
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candidate_labels_urgent = ['Urgent', 'not Urgent'] |
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model="SpamUrgencyDetection" |
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clf = pipeline("zero-shot-classification", model=model) 32 |
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def predict(text): |
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p_spam = clf(text, candidate_labels_spam)["labels"][0] |
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p_urgent = clf(text, candidate_labels_urgent)["labels"][0] |
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return p_spam,p_urgent |
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import pandas as pd |
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df = pd.read_csv("test.csv") |
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texts=df["text"] |
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for i in range( len(texts)): |
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print(texts[i],predict(texts[i])) |
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