HI
how weights are used for prediction the only thing I see is whenever we need to predict we used model ypred_valid =  torch.(model(valid_images)) where model is architecture of my NN.
for index,(valid_images,valid_labels) in enumerate(validation_loader):
    valid_images = valid_images.to(device)
    valid_labels = valid_labels.to(device).float()
    ypred_valid =  torch.sigmoid(model(valid_images))

Usually I have multiple weights for same model So how I need to combine different models weights with same model architecture.
Thanks.!!