RDBT [Anima]
A general finetuned model, better overall quality, better prompt adherence, less artifacts and errors.
Dataset contains ~10k images, handpicked by professional amateur artists, captioned by latest LLM. Accurate body/hands anatomy. Complete background.
Some cover images look ridiculous; they're just for demonstration purposes for corner cases.
Update log and version info: link.
For advanced users: RDBT model is trained as LoRA natively. link.
Usage:
Settings:
Base version: has a suffix "base". Not distilled. CFG 4 and steps 24+ is recommended.
Distilled version: CFG: 1~3. Steps: 16+. Disable CFG (CFG 1) = run the model 2x faster. Cover images are without CFG for demonstration. "RenormCFG" node is highly recommended if CFG is enabled (CFG > 1), set "renorm_cfg" value to 1.1.
Sampler: Euler (best diversity), Euler a/er_sde etc. (better stability)
Res: 1MP
Prompt:
Always specify @style in prompt, or use a style LoRA. Otherwise, you will get random/mixed style.
Quality tags:
Omit ALL quality tags. The fine-tuning dataset has higher quality than "masterpiece". Thus quality tags don't have effects. Omitting those redundant tokens allows LLM to pay more attention on other words.
FAQ:
Why I won't bake a default style:
If a model has a "default" style (ignores prompt and is always active). We call it "overfitted". Technically, it's not a feature, it's a bug. This means the training dataset is not big enough, and the model has lost its ability to generate other styles. I know some default styles look very cool, but this is not my goal.
The goal of RDBT model is to "perfectly" reproduce styles. As some of you know, I use this model to aid in drawing. I need uniqueness (diversity) and consistency in style.
This model has excellent compatibility. You can stack any type of Lora on it. After all, it's you who decide what style you want, not me.
RDBT can't remove nor resist overwhelming Al slop effects
Too long, see: link.
Training data and why it works
AI model is a garbage in, garbage out. What we want are production wallpaper level images. While the Danbooru dataset is massive, high-quality data is extremely scarce. 99.99% imgs are "incomplete" because artists are lazy drawing is hard. Leaving rough outlines, incomplete backgrounds, etc. Therefore the model will also generates "incomplete" images. I "fixed" this by training the model with 100% "complete" imgs.
Sharing merges using this model is not allowed.
This mode is a free and it will always be free. This "restriction" won't affect anyone. It's only aimed at those who steal others' models to sell.
Known model thieves: NukeA.I (selling this model behind paywall on tensorart).
Because he is such a jerk I wrote a story about it. Also contains a guide for trainers about "how to bake special trigger word into your model".