Justin Pinkney

Awesome Pretrained StyleGAN

I maintain two collections of links to StyleGAN models pre-trained on a variety of datasets:

Most of these have been shared via the very active StyleGAN creative community on twitter, and if you're aware of any others then please send them my way. Either create an issue or fill out one of the following forms:

Pretrained models are useful for lots of things #

Speed up model training with transfer learning #

Apart from just generating some example image of whatever the model was trained on, pre-trained models are a super useful for training your own model using transfer learning.

If you want to train a model which is similar to an existing one, for example Ukiyo-e faces then taking a pre-trained model as your starting point to get you some decent results within just a few hours rather than days of training time.

Get weird results with intermediate models and mixing #

Transfer learning (aka fine-tuning) also sometimes gives you some pretty interesting results just as the model starts to transform the generated images from the original objects to the new thing you're training for. See a couple of nice examples below.

https://www.twitter.com/Norod78/status/1255200236181630979 https://www.twitter.com/mmariansky/status/1226756838613491713

In fact you can go further and combine two models, one which has been fine-tuned from another and either do weight averaging or layer swapping to effectively mix the outputs.

Do experiments and investigate the properties of a latent space #

Pre-trained models can also be useful if you want to investigate the properties of specific modifications and manipulations of a trained GAN. In fact my Awesome StyleGAN made and appearance in the excellent GANSpace paper.

A well trained model is also useful if you just want to mess around with the internals of StyleGAN,

Maybe transfer learning will become the standard way to train a GAN #

Transfer learning is currently a very active area of research in the world of GANs, in particular there have been a bunch of publications recently looking at methods for preventing the discriminator from over-fitting when you only have a small dataset. These would seem to make it possible to get very good results using a pre-trained model and only a small amount of data.

Contribute! #

If you have a StyleGAN model you'd like to share I'd love it if you contribute to the appropriate repository. In particular I see lots of users of RunwayML sharing links to their models on Runway, but not sharing the .pkl files, please set those models free!