The base classes [PreTrainedModel], [TFPreTrainedModel], and
[FlaxPreTrainedModel] implement the common methods for loading/saving a model either from a local
file or directory, or from a pretrained model configuration provided by the library (downloaded from HuggingFace's AWS
S3 repository).
[PreTrainedModel] and [TFPreTrainedModel] also implement a few methods which
are common among all the models to:
- resize the input token embeddings when new tokens are added to the vocabulary
- prune the attention heads of the model.
The other methods that are common to each model are defined in [~modeling_utils.ModuleUtilsMixin]
(for the PyTorch models) and [~modeling_tf_utils.TFModuleUtilsMixin] (for the TensorFlow models) or
for text generation, [~generation.GenerationMixin] (for the PyTorch models),
[~generation.TFGenerationMixin] (for the TensorFlow models) and
[~generation.FlaxGenerationMixin] (for the Flax/JAX models).
[[autodoc]] PreTrainedModel - push_to_hub - all
[[autodoc]] modeling_utils.ModuleUtilsMixin
[[autodoc]] TFPreTrainedModel - push_to_hub - all
[[autodoc]] modeling_tf_utils.TFModelUtilsMixin
[[autodoc]] FlaxPreTrainedModel - push_to_hub - all
[[autodoc]] utils.PushToHubMixin
[[autodoc]] modeling_utils.load_sharded_checkpoint