🌍Auto Classes

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 AutoConfig, AutoModel, and AutoTokenizer will directly create a class of the relevant architecture. For instance

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model = AutoModel.from_pretrained("bert-base-cased")

will create a model that is an instance of BertModel.

There is one class of AutoModel for each task, and for each backend (PyTorch, TensorFlow, or Flax).