BB95 Furry Mix

Name: BB95 Furry Mix - v11.0 SE
Rating: 0 (0 reviews)
Author: Bumblebee95

CHECKPOINT

Original

Bumblebee95

Updated: Jun 12, 2024 10:34 AM

Run29K

V12.0 RELEASED : This version is a small improvements of v11SE, so nothing more to say. Will be better than v11SE.

This version has a baked in VAE.

Please consider supporting me so I can continue to make more models --> https://www.patreon.com/BB95FurryMix

Don't forget to join the Furry Diffusion discord server --> https://discord.gg/furrydiffusion

Since v3, this model uses e621 tags.

This model is a mix of various furry models.

It's doing well on generating photorealistic male and female anthro, SFW and NSFW.

I HIGHLY recommend to use Hires Fix to have better results

Below is an example prompt for the v7/v6/v5/v4/v3/v2.

Positive:

anthro (white wolf), male, adult, muscular, veiny muscles, shorts, tail, (realistic fur, detailed fur texture:1.2), detailed background, outside background, photorealistic, hyperrealistic, ultradetailed,

Negative:

I recommend to use boring_e621, you can add bad-hands-v5 if you want

Settings :

Steps: 30-150

Sampler: DDIM or UniPC or Euler A

CFG scale: 7-14

Size: from 512x512 to 750x750 (only v4/v5/v6/v7)

Denoising strength: 0.6

Clip skip: 1

Hires upscale: 2

Hires steps: 30-150

Hires upscaler: Latent (nearest)

Version Detail

Uploaded

Sep 14, 2023 12:30 PM

Base Model

SD 1.5

Steps

60000

Epoch

Description

This is a Special Edition of BB95. It's trained on a small, curated dataset of very high quality images, with the hope of improving the composition quality. Most of the time, it will be better than v11. But in some cases, it will be worse than v11. It's not good enough to be a full, proper v12 with the kind of quality that's expected. It's a side-grade from v11. In testing, it did better at higher resolutions, and the composition was better. Give it a try, see if you like it, and leave a review! If a lot of people say that it's an improvement, maybe the training can continue on a larger dataset. Thanks to Dogarrowtype for the idea, and for helping me collect the dataset.