Pytorch transfer learning predictions
I have been following the pytorch transfer learning tutorial,and following the tutorial to my own dataset i have arrived at this 

model_conv = train_model(model_conv, criterion, optimizer_conv,
                     exp_lr_scheduler, num_epochs=25)

Epoch 1/1
......
......
......
Epoch 24/24
train Loss: 0.8674 Acc: 0.5784
val Loss: 1.2930 Acc: 0.4583
Training complete in 43m 24s
Best val Acc: 0.486111


The tutorial ends here,but im not exaclty sure how do i get predictions for my new images?

Any suggestions would be really helpful.
Thanks in advance.

Simply feed the new image (in the same format as the images in your training dataset were) to the model:

labels = model_conv(new_images)

