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
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 or TensorFlow).