I will be teaching a class of about 18 students. Each student will need to train their own StyleGAN2 model towards the end of the semester and I'm trying to figure out which platform I want them to use. These students will be coming from different disciplines and so ideally we'd use something like Google Colab because then they could easily work off of my code, avoid learning how to ssh into a virtual machine, using bash commands, etc. And for context, this is not a technical course so I'm more concerned with ease of use than having a detailed introduction to using a virtual/remote machine. The other parts of this course involve more reading & discussion on the history of Generative Art. So I see training their own model as a chance to bring in a hands-on approach to thinking with and about Machine Learning in a creative context. I can propose a budget to my institution so it is possible that I use a paid platform (although logistically, it may be more difficult to figure out how to allocate funds to different accounts). I've looked at Paperspace's Gradient tool as well. I know apps like RunwayML would allow students to train a model code-free, but my concern is that Runway uses transfer learning and I kind of want them to only train the model on their own data that they've collected. I'm curious if any of you have suggestions or anecdotes from your own personal experience using different platforms. Thanks in advance!