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My hunch is that is the result of this: https://github.com/CompVis/stable-diffusion#weights
> 515k steps at resolution 512x512 on "laion-improved-aesthetics" (a subset of laion2B-en, filtered to images with an original size >= 512x512, estimated aesthetics score > 5.0
https://github.com/LAION-AI/laion-datasets/blob/main/laion-a... for more details.
What's remarkable is this: https://github.com/LAION-AI/laion-datasets/blob/main/laion-a...
That aesthetic predictor was apparently trained on only 4000 images. If my thinking is correct, imagine the impact those 4000 ratings have had on all of the output of this model.
You can see samples (some NSFW) of different images from the original training set in different rating buckets here, to get an idea of what was included or not in those training steps. http://3080.rom1504.fr/aesthetic/aesthetic_viz.html
My hunch is that is the result of this: https://github.com/CompVis/stable-diffusion#weights
> 515k steps at resolution 512x512 on "laion-improved-aesthetics" (a subset of laion2B-en, filtered to images with an original size >= 512x512, estimated aesthetics score > 5.0
https://github.com/LAION-AI/laion-datasets/blob/main/laion-a... for more details.
What's remarkable is this: https://github.com/LAION-AI/laion-datasets/blob/main/laion-a...
That aesthetic predictor was apparently trained on only 4000 images. If my thinking is correct, imagine the impact those 4000 ratings have had on all of the output of this model.
You can see samples (some NSFW) of different images from the original training set in different rating buckets here, to get an idea of what was included or not in those training steps. http://3080.rom1504.fr/aesthetic/aesthetic_viz.html
You can run craiyon / dalle-mini on a card with 8GB of VRAM if you decrease batch size to 1 and skip the CLIP step. Takes about 7 sec to generate an image on a 3070.
I started with https://github.com/borisdayma/dalle-mini/blob/main/tools/inf... and pared it down.