Note: Random update, random quality. Check the Update Log section.
RDBT [Anima]
Finetuned + distilled for better stability and quality.
Sharing merges using this model is not allowed. This is a distilled model. If you think this LoRA is useful, please share the link or the LoRA file.
Usage:
Base ckpt:
The base ckpt that trained the LoRA is pretrained anima base ckpt. Official HF link.
If you just want a "finetuned base ckpt" and forget about LoRA, you can download this ckpt, which has merged the LoRA.
Prompt
Prefer natural language prompt. Prompt structure: style, subject, action, background.
There are two "rough" trigger words:
"digital anime illustration": 2d anime.
"digital art", 2d art but not anime, mostly digital art. (not many samples)
Style:
This model does not provide a stable default style, so you need to specify style in prompt.
If the style effect is weak without cfg (cfg 1), try cfg 2. Or use a style LoRA, which usually don't need trigger words thus always have full effect.
Quality tags:
You can omit all the quality tags. 1) The quality of training data is higher than "masterpiece". 2) Quality tags have been reinforced during distillation. Thus they don't have noticeable effects.
Same as negative tags. If you use cfg, there is no need to dump "score_1, blurry, worst quality, jpeg artifacts, extra arms,... x100 words" in your negative prompt. Those things have been distilled out.
Recommended settings:
sampler: "euler_a" "euler" "er_sde".
steps: dmd2 distilled: 8~16. cfg distilled: 20~30.
cfg scale: 1~2. Prefer cfg 1 (disable cfg, smooth sampling process, 2x faster). Enable cfg (cfg >1) if you need higher prompt adherence (e.g. style is too weak). High cfg is not necessary. Cover images are all using cfg 1.
cfg distillation and dmd2:
cfg distilled model has stable sampling process. Less deformed or oversimplified images.
dmd2 = cfg + step distillation (aka. low step distillation, turbo). Higher stability, quality and needs less sampling steps.
Update log
[base model version] [finetuned model version] [distillation method] [distillation version]
f = finetuned, cfg = cfg distilled, dmd2 = distribution matching distillation.
N-step dmd2: N means the model can output an image without noise after N steps. It's not a mandatory fixed setting. It's a lower limit. You can always use >N steps. Lower N = stronger distillation.
Recommended versions:
p3 v0.24f dmd2 b: 16-step dmd2.
p3 v0.24f cfg b: close to vanilla anima.
p2 v0.23f dmd2 b: 4-step dmd2. +200% stability
===============
(4/14/2026) p3 v0.24f dmd2 b: Comparing with "v0.24f dmd2": Images should be sharper.
(4/11/2026) p3 v0.24f cfg b: Improved stability and diversity, comparing with previous 0.24f cfg.
(4/10/2026) p3 v0.24f dmd2: roughly 12~16 steps distillation. This is intentional. Low steps distillation = ai slop style without complex texture.
(4/8/2026) p3 v0.24f cfg: Rebased on preview3. Finetuned base model has -40% steps than v0.23. Less overfitted (?).
(4/4/2026) p2 v0.23f dmd2 b: Different distillation settings. Almost a 4 steps dmd2. Maximum stability.
(4/4/2026) p2 v0.23f dmd2: 8 steps dmd2. First dmd2 anima (?).
(3/28/2026) p2 v0.23f cfg: Rebased on preview2. Distillation: improved small details and stability (removed a regularization in distillation target and changed to second-order method).
Voting result: v0.20fd won. Thanks for the feedbacks.
(3/24/2026) preview1 v0.20f cfg b: Distillation: Different settings optimized for anime, high contrast and saturation.
(3/23/2026) p1 v0.20f cfg: Dataset: More furry. Finetuned base model: from v0.12 + more 100% steps. Distillation: Fixed noisy pixels this time, really.
(3/14/2026) preview v0.19f cfg b:
Updated dataset. Some private datasets have been dropped. You might notice the style changed.
Fixed high-freq artifacts in v0.12, now you should get a clear image without noisy pixels
b: Testing new distillation settings. Higher contrast. Aligned with common anime art.
(2/19/2026) preview v0.12f cfg:
Better stability and details, extended dataset.
(3/8/2026) preview v0.11f cfg 512px:
Prove of concept version for v0.12. Same dataset and settings as v0.12, except it was trained with 512px res.
Released by request, as it might be very useful. Running model in 512px and cfg1 is extremely fast (x10 faster, e.g. 30s -> 3s). If you don't have a beefy GPU. You can use this version to test your ideas/prompts in few seconds.
(2/12/2026) preview v0.6 cfg:
CFG distilled only. No finetuning. Cover images are using Animeyume v0.1.
(2/3/2026) preview v0.2f cfg:
Speedrun attempt, mainly for testing the training script. Limited training dataset. Only covered "1 person" images plus a little bit of "furry". But it works, and way better than what I expected.