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* Generation doc * MBartForConditionalGeneration (#6441) * add MBartForConditionalGeneration * style * rebase and fixes * add mbart test in TEST_FILES_WITH_NO_COMMON_TESTS * fix docs * don't ignore mbart * doc * fix mbart fairseq link * put mbart before bart * apply doc suggestions * Use hash to clean the test dirs (#6475) * Use hash to clean the test dirs * Use hash to clean the test dirs * Use hash to clean the test dirs * fix * [EncoderDecoder] Add Cross Attention for GPT2 (#6415) * add cross attention layers for gpt2 * make gpt2 cross attention work * finish bert2gpt2 * add explicit comments * remove attention mask since not yet supported * revert attn mask in pipeline * Update src/transformers/modeling_gpt2.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/modeling_encoder_decoder.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Sort unique_no_split_tokens to make it deterministic (#6461) * change unique_no_split_tokens's type to set * use sorted list instead of set * style * Import accuracy_score (#6480) * Apply suggestions from code review Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Address comments * Styling * Generation doc * Apply suggestions from code review Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Address comments * Styling Co-authored-by: Suraj Patil <surajp815@gmail.com> Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> Co-authored-by: gijswijnholds <gijswijnholds@gmail.com> Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
55 lines
1.7 KiB
ReStructuredText
55 lines
1.7 KiB
ReStructuredText
Models
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----------------------------------------------------
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The base classes :class:`~transformers.PreTrainedModel` and :class:`~transformers.TFPreTrainedModel` implement the
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common methods for loading/saving a model either from a local file or directory, or from a pretrained model
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configuration provided by the library (downloaded from HuggingFace's AWS S3 repository).
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:class:`~transformers.PreTrainedModel` and :class:`~transformers.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 :class:`~transformers.modeling_utils.ModuleUtilsMixin`
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(for the PyTorch models) and :class:`~transformers.modeling_tf_utils.TFModuleUtilsMixin` (for the TensorFlow models) or
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for text generation, :class:`~transformers.generation_utils.GenerationMixin` (for the PyTorch models) and
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:class:`~transformers.generation_tf_utils.TFGenerationMixin` (for the TensorFlow models)
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``PreTrainedModel``
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~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.PreTrainedModel
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:members:
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``ModuleUtilsMixin``
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~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_utils.ModuleUtilsMixin
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:members:
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``TFPreTrainedModel``
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~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFPreTrainedModel
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:members:
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``TFModelUtilsMixin``
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~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_utils.TFModelUtilsMixin
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:members:
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Generative models
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~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.generation_utils.GenerationMixin
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:members:
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.. autoclass:: transformers.generation_tf_utils.TFGenerationMixin
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:members: |