Greetings!
I’ve had great success with building multi-class, single-label classifiers as described in the official PyTorch transfer learning tutorial 150. I have a couple of use cases that require a multi-label image classifier, and I was wondering whether/how I could use the same pre-trained model (e.g. ResNet-101) to train a multi-label classifier. I understand that I need to use a different loss function, but I’m not sure how I can get the resulting model to generate multi-label predictions.