36 lines
888 B
Python
36 lines
888 B
Python
from transformers import pipeline
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pipe = pipeline('text-classification', model="olczig/irony-polish-detection", tokenizer = "olczig/irony-polish-detection")
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def irony_prediction(data):
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result = pipe(data)
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return result
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def clear_data(data):
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data = [i.replace('#','').
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replace('@','').
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replace('\uf8ff','').
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replace('\t','').
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replace('\"','').
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replace('\U000fe329','').
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replace('\U000fe35b','').
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replace('\U000fe4ef','').
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replace('\U000fe341','')
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for i in data['sentences']]
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return data
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def count_predictions(predictions):
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l0 = 0
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l1 = 0
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all = {}
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for i in predictions:
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if i['label'] == 'LABEL_0':
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l0 += 1
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if i['label'] == 'LABEL_1':
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l1 += 1
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all['irony'] = l1
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all['non_irony'] = l0
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return all |