Updated: Oct 21, 2026
base model
Update log and version info: link.
RDBT [Anima]
A general finetuned model, from a personal all-in-one dataset, mainly for digital art and drawings, focusing on lighting and textures, from wallpaper level digital art to 5-min sketch.
Dataset contains ~10k images, handpicked by professional amateur artists. The criteria for evaluation are not visual appeal, but the drawing technique and the level of completion.
Images are captioned by LLM. There is no trigger words or style tags. I'm too lazy to classify them. (TBH, most of the style can't be classified in just few words. It's hard to describe art.). So I used dynamic high caption drop rate hoping the model can guide itself from it's high noise steps.
Some cover images look ridiculous; they're just for demonstration purposes for corner cases.
Useful links:
RDBT | Digital Art: My merged 16-step ckpt optimized for digital anime art. 4x faster. Easy to prompt.
RDBT | Original LoRA: LoRA files for advanced users.
16-step Acc LoRA: Style friendly, less AI slop, compared to the official Turbo.
Usage:
Settings:
Base version: CFG 4 and steps 24+.
Distilled version(8s, 16s, discontinued): CFG: 1. Steps: 8 or 16.
Prompt:
Always specify @style in prompt, or use a style LoRA. Otherwise, you will get random/mixed style.
Unlike most finetuned models out there. This model does not have overfitted default style. Because the dataset is big enough. It's a feature not a bug (see below FAQs).
Quality tags:
You don't need 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.
FAQs:
Why doesn't this model have a default style?
If a model has a "default" style (ignores prompt and is always active). We call it "overfitted". Technically, "default" style is 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.
The goal of RDBT model is to reproduce styles, not one style, but every style, as accurate as possible. As some of you know, I use this model to aid in drawing. I need unique textures and details, instead of uniformed 2.5D AI slop style.
You decide what style you want, not me.
RDBT can't remove nor resist overwhelming Al slop effects
Too long, see: link.
You still haven't mentioned what LoRA can actually do
AI only mimics the training dataset (unless RL, that's different topic). So there is no such thing called "LoRA functionality". If you really want a straight answer:
You can use it as a "regulator/stabilizer/detailer/whatever" LoRA with strength (0.2~0.5). It can alleviate the overfitting from other style LoRAs.
Or higher strength if you want some spicy visual effects. (I use it at full strength with my other style LoRAs)
Why can it be a "stabilizer", why does it work?
Most of styles LoRAs are overfitted, because the training dataset is not big enough (e.g. <50). "Overfitting" means that the model tries to memorize the training data instead of learning the logic within it. This causes various logical errors (hand, pose, background, etc.).
This LoRA is from a much bigger dataset, and focusing on hand, pose etc. It forces the base ckpt focus more on logic. And alleviates (note: not fixes) the overfitting problem.
However, to reiterate, this is not a "feature", but rather a coincidence that it can be used this way. LoRAs that trained on "large" datasets all have similar effects, such as SFT and Turbo
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".