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Update README.md

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@@ -88,7 +88,7 @@ preds = torch.softmax(logits / 0.07, dim=1).squeeze(0).tolist()
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  # Output predictions
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  for i, prompt in enumerate(prompts):
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- print(f"Probability: {preds[i]*100:.3f}%, Text: {prompt}")
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  ```
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  Repeat the process for any other classification tasks you want, such as malware classification and cryptographic algorithm identification, by loading the respective datasets and defining the relevant natural language prompts.
 
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  # Output predictions
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  for i, prompt in enumerate(prompts):
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+ print(f"Probability: {preds[i]*100:.3f}%, Text: {prompt}")
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  ```
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  Repeat the process for any other classification tasks you want, such as malware classification and cryptographic algorithm identification, by loading the respective datasets and defining the relevant natural language prompts.