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Update README.md

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@@ -25,8 +25,7 @@ model = RobertaForSequenceClassification.from_pretrained('s-nlp/roberta_first_to
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  batch = tokenizer.encode("You are amazing!", return_tensors="pt")
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  output = model(batch)
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- predicted_label = torch.sigmoid(output.logits).argmax().item()
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- # 0 for neutral, 1 for toxic
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  ```
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  ## Citation
 
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  batch = tokenizer.encode("You are amazing!", return_tensors="pt")
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  output = model(batch)
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+ # idx 0 for neutral, idx 1 for toxic
 
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  ```
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  ## Citation