Want to support my work or help fund the training of this dataset on other models? Join the Patreon in my profile, and if you do - thank you!
Want SNOFS as a checkpoint instead of a LoKR? https://civarchive.com/models/2416142/snofs-sex-nudes-and-other-fun-stuff-merged
Krea 2 V1.4:
I did some stuff that should help with using SNOFS in combination with other loras. For most generations textures should also be further improved.
Krea 2 V1.3D:
Alright, alright. I figured out a way to greatly restore texture back. It wasn't more training or different settings, and that's all I'm going to say about it. I deserve to have some trade secrets, no? I made it version 1.3D because the D stands for detail. It was actually try F, as in I was totally...frustrated...with how many lengthy tries it took.
Anyways, I had versions that took it further but it tended to have more broken anatomy. So, the same rules still apply if you want something to look like a photo:
Be sure to mention that it's a photo/photograph in the prompt. Do NOT use "photorealistic" or any other term that doesn't actually mean a photo. Krea 2 was trained on a ton of artwork so using any of those types of terms will yeet it back to bad texture.
Some rare prompts might still want to go over to the anime-side, but I still have the photo slider directly on SNOFS Krea. Simply set it to somewhere around .5-2 on the strength and you're probably golden. This was trained on SNOFS 1.2 so I'll be putting out an updated version at some point:
https://civarchive.com/models/2823820/photodetail-slider-for-snofs-krea
The same goes for some specific terms. When in doubt, use the words listed below instead of their synonyms.
My two-stage sampler is still handy for multiple reasons:
https://github.com/Auryg/Krea-2-Two-Stage-Sampler
The idea for the two-stage sampler that you can generate without the turbo lora for the first bit, which helps with variation and prompt adherence, and then bump to a second stage with the turbo lora to keep things fast. For the three-stage variation, you can then bump back to doing it without the turbo lora for the last bit if you want to use a negative prompt. You can also generate at a lower resolution to start and then bump it up.
Also, please, for the love of god try SNOFS by itself before you go adding a bunch of other general NSFW loras or models to it that screw up anatomy.
Ideogram:
Ideogram model has been updated, and is available here: https://civarchive.com/models/2781404/sex-nudes-other-fun-stuff-ideogram-snofs
General Information:
SNOFS was trained on natural language (or JSON, for Ideogram), not tags. It will work best if you use full sentences to describe what you want.
Not using ComfyUI/your inference software doesn't support lokr? I've put up a merged version here. You can also use the merged base model to train off of: https://civarchive.com/models/2416142/snofs-sex-nudes-and-other-fun-stuff-flux-2-klein-9b-base-and-distilled
Here's a list of some of the terms that work well:
anus
blowjob
boudoir
condoms
deepthroat
braless
cowgirl position
cum
cunnilingus (be specific and maybe put kissing in the negative prompt)
deepthroat
dildo
doggystyle position
fingering (anal and vaginal)
hand in panties
handjob
hitachi magic wand
implied blowjob
ipcam / nightvision ipcam
masturbating (might want to put penis in negative prompt, or specify what she's rubbing for women)
massage
missionary position
naked, nude, etc.
penis
pregnant (and can specify trimester)
prone position
reverse cowgirl position
sex
sheer
snapchat (and caption/text/etc)
selfie (and mirror selfie)
spooning position
strap-on dildo
tentacles
licking testicles
undressing
vagina
wet clothes
Depending on the version, the following might work:
anal sex
anilingus
But also keep in mind that it was trained on stuff like "her panties are pulled down to her thighs," not "panty pull."
These models are under the following license:
https://huggingface.co/Ashen3/SNOFS
Flux 2 Klein 9b V1.4:
Additional training. Some of the training was done using https://github.com/BuffaloBuffaloBuffaloBuffalo/ai-toolkit-perceptual , training against depth. Considering how much of SNOFS is two people intermingled with close skin colors, it seemed like a novel idea. It did seem to rapidly help with that sort of thing. On the downside, it seemed to create a bit of a texture issue on very close up images. I did some more training after to try to bring that back and was somewhat successful, but I think I'd need to increase the weight decay to really make that happen. Since everything else was in a good state I decided to release as-is. If you do have that texture issue, try adding "goosebumps" as a negative prompt.
Description
More training along with selective regularization



















