support export push_to_hub #2183
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@ -106,6 +106,10 @@ class ModelArguments:
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default=False,
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metadata={"help": "Whether or not to save the `.bin` files instead of `.safetensors`."}
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)
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export_hub_model_id: Optional[str] = field(
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default=None,
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metadata={"help": "The name of the repository if push the model to the Hugging Face hub."}
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)
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def __post_init__(self):
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self.compute_dtype = None
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@ -50,7 +50,7 @@ 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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model.config.use_cache = True
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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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else:
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@ -62,11 +62,20 @@ def export_model(args: Optional[Dict[str, Any]] = None):
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max_shard_size="{}GB".format(model_args.export_size),
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safe_serialization=(not model_args.export_legacy_format)
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)
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if model_args.export_hub_model_id is not None:
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model.push_to_hub(
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model_args.export_hub_model_id,
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token=model_args.hf_hub_token,
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max_shard_size="{}GB".format(model_args.export_size),
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safe_serialization=(not model_args.export_legacy_format)
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)
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try:
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tokenizer.padding_side = "left" # restore padding side
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tokenizer.init_kwargs["padding_side"] = "left"
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tokenizer.save_pretrained(model_args.export_dir)
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if model_args.export_hub_model_id is not None:
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tokenizer.push_to_hub(model_args.export_hub_model_id, token=model_args.hf_hub_token)
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except:
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logger.warning("Cannot save tokenizer, please copy the files manually.")
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