  Super-Selfish is an easy to use PyTorch framework for image-based
self-supervised learning. Features can be learned with 13 algorithms that span
from simple classification to more complex state of theart contrastive pretext
tasks. The framework is easy to use and allows for pretraining any PyTorch
neural network with only two lines of code. Simultaneously, full flexibility is
maintained through modular design choices. The code can be found at
https://github.com/MECLabTUDA/Super_Selfish and installed using pip install
super-selfish.
