diff --git a/src/transformers/modeling_utils.py b/src/transformers/modeling_utils.py index cc7d0bea330e..746bcfb9d2a4 100644 --- a/src/transformers/modeling_utils.py +++ b/src/transformers/modeling_utils.py @@ -1487,12 +1487,6 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P Please refer to the mirror site for more information. _fast_init(`bool`, *optional*, defaults to `True`): Whether or not to disable fast initialization. - low_cpu_mem_usage(`bool`, *optional*, defaults to `False`): - Tries to not use more than 1x model size in CPU memory (including peak memory) while loading the model. - This is an experimental feature and a subject to change at any moment. - torch_dtype (`str` or `torch.dtype`, *optional*): - Override the default `torch.dtype` and load the model under this dtype. If `"auto"` is passed the dtype - will be automatically derived from the model's weights. @@ -1502,6 +1496,12 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P + low_cpu_mem_usage(`bool`, *optional*, defaults to `False`): + Tries to not use more than 1x model size in CPU memory (including peak memory) while loading the model. + This is an experimental feature and a subject to change at any moment. + torch_dtype (`str` or `torch.dtype`, *optional*): + Override the default `torch.dtype` and load the model under this dtype. If `"auto"` is passed the dtype + will be automatically derived from the model's weights. kwargs (remaining dictionary of keyword arguments, *optional*): Can be used to update the configuration object (after it being loaded) and initiate the model (e.g., `output_attentions=True`). Behaves differently depending on whether a `config` is provided or