HuggingFace Diffusers is Apache and supports Diffusion Transformers: https://huggingface.co/docs/diffusers/en/api/pipelines/dit

They are actually based on the Attribution - Non-commercial Facebook code and have the same license.

Are you sure about that? https://github.com/huggingface/diffusers lists the Apache 2 license.

Pretty sure that license header ended up in the codebase from a clever guy making a PR or it was just a mistake.

Unfortunately this statement would not offer sufficient legal protection, so the original authors would have to be convinced to give up their previous rights and change the upstream copyright (and huggingface should update their repo license statement). Of course, these days it is typically easy enough to reimplement the code from a paper in plain pytorch, so I’m not sure one needs all this huggingface repo with the extra framework and risk, but to me it doesnt fit the requirement of the OP question.

Ok, I would like to believe that. That's great then thanks.

If it worries you, maybe open an issue? No sane man would allow a weird license that's an API call away from screwing up your own products.

I opened an issue here: https://github.com/huggingface/diffusers/issues/8306

That's sort of confusing (to me at least) because that particular header also lists MIT and Apache licenses.

Besides huggingface there's also the DDPT repo: https://github.com/lucidrains/denoising-diffusion-pytorch/

Nice. But is that a diffusion transformer?

I believe it's got one, yes: https://github.com/lucidrains/denoising-diffusion-pytorch/bl...

I found this:

https://paperswithcode.com/paper/scalable-diffusion-models-w...

https://github.com/mindspore-lab/mindone/tree/master/example...