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emiliosheinz
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6b02e3d
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Parent(s):
43d8e37
create app.py with static string comparison
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app.py
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("distilbert-base-multilingual-cased")
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model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-multilingual-cased")
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# example sentences
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sentence1 = "O Brasil é o maior país da América do Sul"
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sentence2 = "A Argentina é o segundo maior país da América do Sul"
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# tokenize the sentences
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inputs = tokenizer(sentence1, sentence2, padding=True, truncation=True, max_length=250, return_tensors="pt")
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# get the output logits for the sentence pair classification task
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outputs = model(**inputs).logits
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# calculate the softmax probabilities for the two classes (similar or dissimilar)
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probs = outputs.softmax(dim=1)
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# the probability of the sentences being similar is the second element of the output array
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similarity_score = probs[0][1].item()
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print("Similarity score:", similarity_score)
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