This is an updated version of Subreddit V3 (https://civarchive.com/models/5308/subreddit-v3), an experimental model trained on a private dataset. Compared to V3, this one can be more easily controlled, gives decent results more consistently, and slightly expands the list of known subreddits. Don't expect the super photorealistic perfection from those top tier models, but hopefully this model is fun to play around with.
Version 6 builds on top of Version 5 by adding aesthetic scores to all the prompts during training. You should now be able to specify your desired aesthetic using "best aesthetic", "normal aesthetic", or "bad aesthetic". This version was trained on more data, 500k images this time, and trained for slightly longer.
Version 5 is now trained at a base resolution of 640x640, along with aspect ratio bucketing into the following resolutions: 448x832, 448x896, 512x768, 576x704, 640x640, 704x576, 768x512, 832x448, 896x448.
The model was trained with prompts of the form "Some kind of caption for the image, r/subreddit, reddit, best quality, normal aesthetic". It knows "best", "high", and "medium" quality. Quality is based on the image's popularity in the dataset. Aesthetic is based on the LAION aesthetic tagger. The model knows the following subreddits:
gonewild
nsfw
RealGirls
cumsluts
LegalTeens
collegesluts
AsiansGoneWild
pussy
milf
adorableporn
ass
Nude_Selfie
pawg
boobs
celebnsfw
bigasses
juicyasians
latinas
GodPussy
Amateur
xsmallgirls
18_19
Gonewild18
asshole
workgonewild
nsfwcosplay
palegirls
paag
asstastic
Upskirt
TooCuteForPorn
TinyTits
FitNakedChicks
altgonewild
traps
FemBoys
GWCouples
Boobies
CuteLittleButts
GirlswithGlasses
assholegonewild
PetiteGoneWild
BDSMYou can mix subreddits by specifying multiple.
Description
Retrained from SD 1.5 for 10,000,000 samples
FAQ
Comments (19)
Model is missing a VAE. What do you recommend?
Should just be the stock SD 1.5 VAE
Trainig a LoRA on v7 fails and gives me error messages. With v6 it works. Please have a look.
There is no description for what V7 adds, beyond the inability to train a Lora with it (as per other comments) Also the sample images are pretty awful compared to older versions... - anything else?
Seems it is trained on 1.5, I will try it and see what it does. The concept has good potential, I do wish it could work.
Without a doubt, the best and most useful base model I use in all my NSFW checkpoint merges. I bake this checkpoint into all my merges because its so good; this is a highly underated model.
About what portion of your final models would you say this ends up as, as a percentage, for best results?
Anyone achieved to extract a lora from it? It errors it out for me everytime
I also can't merge Loras to checkpoints that have V7 in the merge... its quite annoying
I got a Lora out of V7 and can train with it.
Download V7 and run this python script to fix it. You will then be able to train on, extract from, and merge with it.
Heads up, will need slight reformating.
Credit for script goes to @AwayWithTheFaeries
python
import sys
import os
from safetensors import safe_open
from safetensors.torch import save_file, load_file
def fix_diffusers_model_conversion(load_path: str, save_path: str):
# load original
tensors = {}
with safe_open(load_path, framework="pt") as f:
for key in f.keys():
tensors[key] = f.get_tensor(key)
# migrate
new_tensors = {}
for k, v in tensors.items():
new_key = k
# only fix the vae
if "first_stage_model." in k:
# migrate q, k, v keys
new_key = new_key.replace(".to_q.weight", ".q.weight")
new_key = new_key.replace(".to_q.bias", ".q.bias")
new_key = new_key.replace(".to_k.weight", ".k.weight")
new_key = new_key.replace(".to_k.bias", ".k.bias")
new_key = new_key.replace(".to_v.weight", ".v.weight")
new_key = new_key.replace(".to_v.bias", ".v.bias")
new_tensors[new_key] = v
# save
save_file(new_tensors, save_path)
if name == "__main__":
fix_diffusers_model_conversion(
os.path.normpath(sys.argv[1]),
os.path.normpath(sys.argv[1] + "_fixed"),
)
```
One of the best on this site, it'd be great to get an update with even more nsfw subreddits added
with the Reddit API changes I doubt it will ever happen
@firedelta5 Spez is a bastard
no love for hairy gurlz?!
So I'm really curious if you're going to make an SDXL model. To this day I don't think any model has done what this one has.
Which brings me to questions if you can answer them. How did you get this dataset? And what was the training like for the original subredditV3? I was blown away over a year ago by what that model did and I still am. Nothing else is like it.
I'm sure you managed to find BiGASP by now?
Be amazing if you aren't intending to train for SDXL to release the dataset you used for others to train.
This has been by far the best nsfw model in 1.5!