SVM after Feature Extraction in PyTorch

In a specific image classification task, I found a paper stating that better results are obtained if the classifier is a SVM instead of the fully-connected layers.

How would I be able to compute this using PyTorch for the feature extraction part (and maybe sklearn for the SVM?) ? Is there any prior examples online?

Thanks in advance!