Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Loading Weights
First things first: To load the weights into our model, we need to retrieve them.
Sure, an easy way of retrieving them would be to set the argument
pretrained=True while creating the model. But you can also download the weights
from a given URL, which gives you the flexibility to use pre-trained weights from
wherever you want!
PyTorch offers the load_state_dict_from_url() method: It will retrieve the
weights from the specified URL and, optionally, save them to a specified folder
(model_dir argument).
"Great, but what’s the URL for AlexNet’s weights?"
You can get the URL from the model_urls variable in
torchvision.models.alexnet:
URL for AlexNet’s Pre-trained Weights
1 url = model_urls['alexnet']
2 url
Output
'https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth'
Of course, it doesn’t make any sense to do this manually for models in PyTorch’s
library. But, assuming you’re using pre-trained weights from a third party, you’d be
able to load them like this:
Loading Pre-trained Weights
1 state_dict = load_state_dict_from_url(
2 url, model_dir='pretrained', progress=True
3 )
508 | Chapter 7: Transfer Learning