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optimize predict vram

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Former-commit-id: a577e44eee351b3ed8011a33ae01cd713354ff97
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hiyouga
2024-08-30 23:08:45 +08:00
parent 66a1abac6a
commit d789b667d7
5 changed files with 10 additions and 10 deletions
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src/llamafactory/train/rm/trainer.py
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@@ -75,8 +75,8 @@ class PairwiseTrainer(Trainer):
return super().create_scheduler(num_training_steps, optimizer)
def compute_loss(
self, model: "PreTrainedModel", inputs: Dict[str, torch.Tensor], return_outputs: bool = False
) -> Union[torch.Tensor, Tuple[torch.Tensor, List[torch.Tensor]]]:
self, model: "PreTrainedModel", inputs: Dict[str, "torch.Tensor"], return_outputs: bool = False
) -> Union["torch.Tensor", Tuple["torch.Tensor", List["torch.Tensor"]]]:
r"""
Computes pairwise loss. The first n examples are chosen and the last n examples are rejected.