(9/26/2026): Distilled ckpt will not be updated. Use the new standalone acc LoRA here. After v2.4. All versions will be the "base" version (not distilled).
Update log and version info: link.
RDBT [Anima]
A general finetuned base 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.
There is no overfitted default style. Because the dataset is big enough. It's a feature not a bug. You must specify @style in prompt, or use a style LoRA. Otherwise, you will get random/mixed style.
If you're not good at mixing LoRAs for a pretrained model, I also released a ckpt that merged many useful things, here. Out-of-the-box high quality, 16-step fast generation.
If you're an advanced user and want to minimax everything: RDBT is trained as LoRA natively: link.
16-step Acc LoRA: link.
Usage:
Settings:
Base version: has a suffix "base". CFG 4 and steps 24+ is recommended.
Distilled version (discontinued): CFG: 1. Steps: 16+.
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.
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 unique textures and details, instead of uniformed 2.5D AI slop 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.
My homemade distillation vs Anima official turbo model:
Official turbo: 8 steps. High stability, low entropy. Adds a strong 2D anime filter that will overwrite style and cause style shifting.
My homemade distillation: 16 steps. High diversity, low stability. Minimal style shifting.
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".
Description
FAQ
Comments (14)
Looks great. Really good work well done 👍. Have a ever considered collaborating with @duongve13112002 to make a solid, stable and high quality Preview 2 checkpoint? As I love preview 1 but the natural language prompt adherence is better especially for more complex scenes and with multiple subjects on P2.
Any examples? I tested p2 and I think prompt adherence is the same as p1, afaik, they were still using tag based captions. And RDBT has better prompt adherence than p2, at cost of built-in styles.
the original p1 does have some stability issues, but it is a "pretrained" model, it should be unbiased and thus unstable. It's ideal for finetuning, but not ideal for users.
I think p2 is a finetuned model, which is difficult to finetune again. Some people said it takes longer to train LoRA on p2, that might be the prove.
@reakaakasky it's been a while since I used it but what is your opinion on NetaYume Lumina aa I think it's great I don't know how it compares to anima tho.
Lumina has way better aesthetics than Cosmos predict 2.
Cosmos predict 2 has better logical understanding.
How are you training these ? LCM ?
just cfg distillation
I see , thank you
Was just curious to try as well.
Tried LCM but it didn't turn out that well , it may need same dataset as original model was trained on.
Works quite well with https://civitai.com/models/2466415/cosmos-predict25-2b-base-distilled-extracted-dmd2-lora at 0.7 strength, 12 steps cfg 1, and https://github.com/pamparamm/ComfyUI-ppm for somewhat working negatives
(silly example prompt: "2girls, kissing (score_9, blushing, :-1.0)" )
very cool
Do you have an fp8 version of anima preview 2?
no, I gave up. it's slower in ComfyUI. fp8 needs torch.compile to inline kernels. Right now torch.compile is unusable, and will be unusable forever if they enforce their dynamic vram mode. On my hardware it's even slower 20% than bf16 +compile.
https://huggingface.co/Bedovyy/Anima-FP8/tree/main
Not mine, not tested, enabled hw fp8, but no calibration metadata.
@reakaakasky Yea, i'm rolling now with silveroxides int8 quant. Slightly faster than fp8 while having basically bf16 quality. 2.34s/it vs. 1.58s/it on my hardware fp16 preview2 vs int8 preview2, no torch compile. Seeds look fairly similar. Btw you were right about klein anime finetune in the making. Apparently chenkin is at it.
. https://huggingface.co/silveroxides/Anima-Quantized/tree/main
@deitychaser I don's see the chenkin klein finetune on their page, or did they just start?
@mc355168 Yea, its still in trainig in testing.
Man all of my lora floading here since your checkpoint is my favorite and use it to generate sample for them lol Still enjoying the checkpoint very much thankfull for it !
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