70 lines
2.2 KiB
Markdown
70 lines
2.2 KiB
Markdown
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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# Models
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The base classes [`PreTrainedModel`], [`TFPreTrainedModel`], and
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[`FlaxPreTrainedModel`] implement the common methods for loading/saving a model either from a local
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file or directory, or from a pretrained model configuration provided by the library (downloaded from HuggingFace's AWS
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S3 repository).
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[`PreTrainedModel`] and [`TFPreTrainedModel`] also implement a few methods which
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are common among all the models to:
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- resize the input token embeddings when new tokens are added to the vocabulary
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- prune the attention heads of the model.
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The other methods that are common to each model are defined in [`~modeling_utils.ModuleUtilsMixin`]
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(for the PyTorch models) and [`~modeling_tf_utils.TFModuleUtilsMixin`] (for the TensorFlow models) or
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for text generation, [`~generation.GenerationMixin`] (for the PyTorch models),
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[`~generation.TFGenerationMixin`] (for the TensorFlow models) and
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[`~generation.FlaxGenerationMixin`] (for the Flax/JAX models).
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## PreTrainedModel
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[[autodoc]] PreTrainedModel
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- push_to_hub
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- all
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## ModuleUtilsMixin
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[[autodoc]] modeling_utils.ModuleUtilsMixin
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## TFPreTrainedModel
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[[autodoc]] TFPreTrainedModel
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- push_to_hub
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- all
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## TFModelUtilsMixin
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[[autodoc]] modeling_tf_utils.TFModelUtilsMixin
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## FlaxPreTrainedModel
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[[autodoc]] FlaxPreTrainedModel
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- push_to_hub
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- all
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## Pushing to the Hub
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[[autodoc]] utils.PushToHubMixin
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## Sharded checkpoints
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[[autodoc]] modeling_utils.load_sharded_checkpoint
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