Update modeling_quiet.py

modeling_quiet.py

@@ -1847,11 +1847,11 @@ class QuietForCausalLM(QuietPreTrainedModel):
                             [shift_labels, padding],
                             dim=-1
                         )
-						# Before converting rm tokens to one-hot, clamp the values to ensure they are within the valid index range
-						new_rm_tokens = torch.clamp(new_rm_tokens, 0, self.vocab_size - 1)
+                        # Before converting rm tokens to one-hot, clamp the values to ensure they are within the valid index range
+                        new_rm_tokens = torch.clamp(new_rm_tokens, 0, self.vocab_size - 1)
 
-						# Now safely convert rm tokens to one-hot
-						probabilities_2d = F.one_hot(new_rm_tokens, num_classes=self.vocab_size).reshape(-1, self.vocab_size).to(probabilities_2d.dtype)
+                        # Now safely convert rm tokens to one-hot
+                        probabilities_2d = F.one_hot(new_rm_tokens, num_classes=self.vocab_size).reshape(-1, self.vocab_size).to(probabilities_2d.dtype)
                     else:
                         continue
                 temperature = self.gumbel_temperature if self.training else 0.001