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AutoModels
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In many cases, the architecture you want to use can be guessed from the name or the path of the pretrained model you are supplying to the ``from_pretrained`` method.
AutoClasses are here to do this job for you so that you automatically retrieve the relevant model given the name/path to the pretrained weights/config/vocabulary:
Instantiating one of ``AutoModel``, ``AutoConfig`` and ``AutoTokenizer`` will directly create a class of the relevant architecture (ex: ``model = AutoModel.from_pretrained('bert-base-cased')`` will create a instance of ``BertModel``).
``AutoConfig``
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoConfig
:members:
``AutoTokenizer``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoTokenizer
:members:
``AutoModel``
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoModel
:members:
``AutoModelForPreTraining``
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoModelForPreTraining
:members:
``AutoModelWithLMHead``
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoModelWithLMHead
:members:
``AutoModelForSequenceClassification``
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoModelForSequenceClassification
:members:
``AutoModelForQuestionAnswering``
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoModelForQuestionAnswering
:members:
``AutoModelForTokenClassification``
~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.AutoModelForTokenClassification
:members:
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