You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I want to use Huggingface's ViTForImageClassification. How do I integrate it in FACIL? I want to load the pretrained model
'google/vit-base-patch16-224'. I have read the instructions to add networks in readme of networks. However I am still not sure how to implement it. How do I set "self.head_var = 'fc'" when head is changed by "model.classifier = nn.Linear(768, num_classes)"? How exactly will a class even be created in this case?
The text was updated successfully, but these errors were encountered:
Not sure I understand which is the exact issue. If the pretrained model has a head called classifier, you just need to define self.head_var = 'classifier' and it should be removed. Not self.head_var = 'fc' because there is no layer called fc.
If you want, you can also remove the head directly from the pretrained model and use the argument --keep-existing-head (even though you removed it) so that nothing else is removed.
I want to use Huggingface's ViTForImageClassification. How do I integrate it in FACIL? I want to load the pretrained model
'google/vit-base-patch16-224'. I have read the instructions to add networks in readme of networks. However I am still not sure how to implement it. How do I set "self.head_var = 'fc'" when head is changed by "model.classifier = nn.Linear(768, num_classes)"? How exactly will a class even be created in this case?
The text was updated successfully, but these errors were encountered: