Remove manully set use_cache; torch_dtype is not str, save model as bfloat16 used to fail;
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@ -56,12 +56,11 @@ def export_model(args: Optional[Dict[str, Any]] = None):
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if not isinstance(model, PreTrainedModel):
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raise ValueError("The model is not a `PreTrainedModel`, export aborted.")
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setattr(model.config, "use_cache", True)
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if getattr(model.config, "torch_dtype", None) == "bfloat16":
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model = model.to(torch.bfloat16).to("cpu")
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if hasattr(model.config, "torch_dtype"):
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model = model.to(getattr(model.config, "torch_dtype")).to("cpu")
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else:
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model = model.to(torch.float16).to("cpu")
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setattr(model.config, "torch_dtype", "float16")
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model = model.to(torch.float32).to("cpu")
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setattr(model.config, "torch_dtype", "float32")
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model.save_pretrained(
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save_directory=model_args.export_dir,
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