There's been a lot happening on SDXL, yes.
> My expectation was that SDXL would probably not see wide adoption for a while because it's hard to make up for the worse training data, is that bearing out?
What worse training data?
Nice! Care to share any projects/advancements/gens you've found particularly compelling if you have anything handy?
> What worse training data?
I don't know this, but I think it's a pretty safe assumption given the state of 2.0/the political climate around this stuff, along with the comparative lower diversity of gens I've seen come out of SDXL. I haven't seen anything to the contrary but I'd love to be wrong.
Where do you read that SDXL has worse training data? They didn't disclose what the model was trained on like the previous models.