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For someone only tangentially familiar with this space, how is this different than e.g. https://github.com/nerdyrodent/VQGAN-CLIP https://github.com/nerdyrodent
by daniel-thompson 4y ago
For someone only tangentially familiar with this space, how is this different than e.g. https://github.com/nerdyrodent/VQGAN-CLIP https://github.com/nerdyrodent/VQGAN-CLIP which you can also run at home? Is it the quality of the generated images?
- barber5 4y agoYes for the end user that will be the main difference. From the curation of the training data to the model itself a number of things have been put together that make the generations substantially more aesthetically pleasing imho
- lxe 4y agoStable diffusion generates outputs that are comparable or better than DALLE, and far beyond what VQGAN can generate.
- andybak 4y agoI must say that some of my favourite images are ones that I generated in VQGAN. Don't dismiss older/smaller models. Some have a very specific quality that is perfect for some things. (Heck, I'm still fond of Aphantasia and it's weird tiling)
- lxe 4y agoI personally prefer Disco Diffusion, but there's no denying stability is beyond anything else when it comes to coherency.
- stellaathena 4y agoStable Diffusion produces substantially higher quality images in most context, but is much more expensive to produce. The genius of VQGAN-CLIP is that it showed that you could take two pre-existing models and combine them to get text-to-image synthesis to work at all. By contrast, models like DALL-E and Stable Diffusion require extremely expensive pretraining. There's a discussion of this in the VQGAN-CLIP paper, see in particular 6.1 "Efficiency as a Value" https://arxiv.org/abs/2204.08583 https://arxiv.org/abs/2204.08583 Disclaimer: I'm one of the authors of the VQGAN-CLIP paper and was tangentially involved with Stable Diffusion.