bigASP 🐍
A photorealistic SDXL model that works with danbooru style tags! This experimental model was finetuned from base SDXL on almost 1.5 MILLION high quality photos for 30 million training samples. Every photo was tagged using JoyTag, a state of the art tagging model that extends the danbooru2021 dataset to photographic content. This imbues bigASP 🐍 with all the expressive prompting power of an anime model, while generating high quality photographic results.
This is my first foray into base SDXL models. I'm excited to see how the community uses this model and to learn its strengths and weaknesses. Please share your gens and feedback!
Features
Danbooru style tag prompting: e.g. photo (medium), 1girl, spread legs, small breasts, nipples, pussy, pantyhose, sheer legwear, couch
Aesthetic/quality score: e.g. score_8_up, score_7, you name it, you got it.
Diversity: Want something other than generic white women in your photo gens? Get ready for male, female, trans, dark skin, light skin, big breasts, small breasts, and everything in between. Paint the world in colors.
Aspect ratio bucketing: Widescreen, square, portrait, bigASP 🐍 is ready to take it all.
High quality training data: Most of the training data consists of high quality, professional grade photos with resolutions well beyond SDXL's native resolution, all downloaded in their original quality with no additional compression. bigASP 🐍 won't miss a single pixel.
Large prompt support: Trained with support for up to 225 tokens in the prompt. It is BIG asp, after all.
Prompting
Building on the shoulders of giants like Pony XL, bigASP 🐍 uses a custom aesthetic/quality model to rate the training dataset and assign scores from 1 to 9. However, you shouldn't need a long "score_9, score_8, score_7" etc prompt. A simple "score_8_up" should suffice in your positive prompt, and a low score or two in your negative like "score_1, score_2".
Score tags should always come first, but all other tags can come in any order (tags were shuffled during training). Underscores or spaces, doesn't matter: e.g. "small breasts" or "small_breasts" both work.
"photo (medium)" should likely be included in every prompt, as all of the training data was photographic. NOTE: You will likely need to use "photo \(medium\)" instead if your UI uses parentheses to weight words! I made the same mistake...
Beyond that, consult your local danbooru for a list of all tags bigASP 🐍 understands. In addition, bigASP 🐍 understands various subreddits, which can be prompted with, for example, "r/asstastic", as well as just "reddit", "onlyfans", and "fansly". Explore and see what bigASP 🐍 can do!
Example prompts:
score_7_up, photo \(medium\), 1girl, spread legs, small breasts, puffy nipples, cumshot, shocked
score_7_up, photo (medium), 1boy, male focus, penis, muscular, testicles, spread legs
score_7_up, photo \(medium\), long hair, standing, thighhighs, reddit, 1girl, r/asstastic, kitchen, dark skin
score_8_up, photo (medium), black shirt, pussy, long hair, spread legs, thighhighs, miniskirt, outside
Limitations
No offset noise: Sorry, maybe next version.
No anime: This is a photo model through and through. Perhaps in a future version anime will be included to expand the model's concepts.
Faces/hands/feet: You know the deal. I can't work miracles.
Undertrained: In my usage so far I've found bigASP to be at least slightly undertrained. I think another 10M or more training samples could get the model to where I really want it.
VAE issues: SDXL's VAE sucks. We all know it. But nowhere is it more apparent than in photos. And because bigASP generates such high levels of detail, it really exposes the weaknesses of the VAE. Not much I can do about that.
An obsession with stone backgrounds?: Dunno why, but a lot of my gens end up with a stone background if I don't prompt for something else. Your guess is as good as mine.
Scoring model: I trained the quality/scoring model from scratch. I find that it works a lot better than the old aesthetic model used by SD and SDXL. It gets images into a general trend of "blurry, lowres reddit selfie garbage" at score_1 up to professional photoshoot at score_9. But it could still benefit from more work so it's less biased towards that photoshoot look.