python
model = T5ForConditionalGeneration.from_pretrained("t5", torch_dtype="auto")
Models instantiated from scratch can also be told which dtype to use with:
python
config = T5Config.from_pretrained("t5")
model = AutoModel.from_config(config)
Due to Pytorch design, this functionality is only available for floating dtypes.
ModuleUtilsMixin
[[autodoc]] modeling_utils.ModuleUtilsMixin
TFPreTrainedModel
[[autodoc]] TFPreTrainedModel
    - push_to_hub
    - all
TFModelUtilsMixin
[[autodoc]] modeling_tf_utils.TFModelUtilsMixin
FlaxPreTrainedModel
[[autodoc]] FlaxPreTrainedModel
    - push_to_hub
    - all
Generation
[[autodoc]] generation_utils.GenerationMixin
[[autodoc]] generation_tf_utils.TFGenerationMixin
[[autodoc]] generation_flax_utils.FlaxGenerationMixin
Pushing to the Hub
[[autodoc]] file_utils.PushToHubMixin
