I wish they had more examples. the image doesn't seem to be that much better than if you generate an image with stable diffusion and then tweak the prompt.
I came up with a similar idea to this (also pre-Dalle edits-via-instruction) with the idea that prompting generators kinda sucks (also chat interfaces for image editing aren't great) and really you just want to explore the latent space "around" an initial prompt.
What's interesting to me is that the project feels very "un-Apple", despite being open-sourced under the Apple org; some typos and lack of proper punctuation in the README, using jupyter notebooks for the data processing instead of scripts or a CLI, poor repo organization, no comments even in the demo: https://github.com/apple/ml-mgie/blob/main/demo.ipynb
Apple truly becoming an ML company when they release ML Engineer quality code ;)
> Notices: Apple's rights in the attached weight differentials are hereby licensed under the CC-BY-NC license. Apple makes no representations with regards to LLaMa or any other third party software, which are subject to their own terms.
Wait, they can do that? Assuming weights have copyright, shouldn't the finetuning be a modification of the original work and so have the same license?
11 comments
[ 3.4 ms ] story [ 23.9 ms ] thread[1] https://www.youtube.com/watch?v=Uj9Jg4WldJg
Here's an overview of the tool (Dreamwalker): https://www.youtube.com/watch?v=k_mJgFmdWWY
And you can download/use it for free here (mac/pc): https://forums.afterschool.studio/t/dreamwalker-alpha-2-rele...
Apple truly becoming an ML company when they release ML Engineer quality code ;)
Wait, they can do that? Assuming weights have copyright, shouldn't the finetuning be a modification of the original work and so have the same license?
https://github.com/timothybrooks/instruct-pix2pix