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app.py
CHANGED
@@ -40,6 +40,7 @@ model = AutoModelForSequenceClassification.from_pretrained(modelPath)
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# RoBERTA: [0]: neutral, [1]: toxic
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encoding = tokenizer.encode(txt, return_tensors='pt')
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result = model(encoding)
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# transform logit to get probabilities
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prediction = nn.functional.softmax(result.logits, dim=-1)
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# RoBERTA: [0]: neutral, [1]: toxic
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encoding = tokenizer.encode(txt, return_tensors='pt')
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result = model(encoding)
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result
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# transform logit to get probabilities
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prediction = nn.functional.softmax(result.logits, dim=-1)
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