for fine_tune I mean, if we want to change last layer size(e.g. number of class), is it still possible?
Let’s say my model is something like that:
class Mymodel(nn.Module):
def init(self, num_classes):
super(Mymodel, self).init()
self.model1 = models.resnet50(pretrained=True)
self._dropout = nn.Dropout(.4)
self.sig = nn.Sigmoid()
self.fc =nn.Linear(2048, num_classes)
…
then what I did is:

train the model
evaluate model
save model using torch.jit.save(net_trace,‘model.pt’)