'vgg16',
'vgg16_bn',
'vgg19',
 'vgg19_bn']
 ```
Note that PyTorch Hub also allows auxillary entrypoints (other than pretrained models), e.g. bertTokenizer for preprocessing in the BERT models, to make the user workflow smoother.
Load a model
Now that we know which models are available in the Hub, users can load a model entrypoint using the torch.hub.load() API. This only requires a single command without the need to install a wheel. In addition the torch.hub.help() API can provide useful information about how to instantiate the model.
print(torch.hub.help('pytorch/vision', 'deeplabv3_resnet101'))
model = torch.hub.load('pytorch/vision', 'deeplabv3_resnet101', pretrained=True)

It is also common that repo owners will want to continually add bug fixes or performance improvements. PyTorch Hub makes it super simple for users to get the latest update by calling:
```python