Merge 8607169546 into 802c15b2b4

model/model_minimind.py

@@ -266,8 +266,7 @@ class MiniMindForCausalLM(PreTrainedModel, GenerationMixin):
             attention_mask = torch.cat([attention_mask, attention_mask.new_ones(attention_mask.shape[0], 1)], -1) if attention_mask is not None else None
             logits = outputs.logits[:, -1, :] / temperature
             if repetition_penalty != 1.0:
-                for i in range(input_ids.shape[0]):
+                for i in range(input_ids.shape[0]): logits[i, torch.unique(input_ids[i])] /= repetition_penalty
-                    seen = torch.unique(input_ids[i]); score = logits[i, seen]; logits[i, seen] = torch.where(score > 0, score / repetition_penalty, score * repetition_penalty)
             if top_k > 0: 
                 logits[logits < torch.topk(logits, top_k)[0][..., -1, None]] = -float('inf')
             if top_p < 1.0: