Will Berman

> Great to hear that you already have it on a branch. Could you maybe add it directly to this PR? Maybe in a next step we could verify that...

PR description is updated to reflect progress on merging full model. Notebook which compares outputs from autoencoder, transformer, and text embedder is here and linked in PR description https://github.com/williamberman/vq-diffusion-notebook. Once...

> @williamberman let me know if you'd like me to review already now or better once the scheduler is integrated as well :-) Let’s wait until the scheduler is integrated....

The working scheduler is on this branch now. Going to do some more cleaning and docs before requesting formal review :)

@patrickvonplaten Ok, I think this is ready for reviews! I updated the notebook to compare latents during the denoising process and to compare the final images. The current model is...

> This PR is already in a great shape! > > The main final change would be to try to use existing modules from `attention.py` to a maximum (by adapting...

@patrickvonplaten Ok, I merged the changes into attention.py so the model uses SpatialTransformer. I tried to follow the existing coding style as best as possible. Let me know if you...

> Hey @williamberman, > > You've really done an amazing job here! Very impressed by how you were able to add such a new complex model into the existing API!...

> @williamberman I am wondering did you try training it or just verified in infer mode? Just inference using the weights microsoft published. Training would have been a good amount...

> @williamberman Thank you for your work! I'm having trouble with exporting my model because of SVD right now. I hope this PR will be done. > > One comment...