(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 (18)
Can you please put your fp16 patch back for download? They might have implemented fp16 support to ComfyUI, but it's almost 3 times slower than your patch on my hardware.
Thank god I saved the patch on my own, here: anina_fp16_patch.py · RicemanT/Loras_Collection at main
Does my patch still work? I didn't test.
I deleted my patch because I thought my patch will mess up their implement.
@reakaakasky it still work yeah, i havent test if comfy is slower or not but i'm literally genning rn so your patch seems safer lol
I don't think my patch is needed. I checked and tested comfyui's patch.
Although I'm on 4xxx, so idk.
"3 times slower" sounds like fp32
@reakaakasky On RTX 2070 with your patch is 1.5 s/it. With your patch removed (ComfyUI's patch) it's 3.2 s/it. (made sure it's fp16 computedtype). More than 2x slower without your patch. Significant difference.
@gannibal do you have the --fast arg in your comfy startup command? My patch also enabled fp16_accumlation.
@reakaakasky My bad, i also had xformers turned on, it did not play well with ComfyUI's patch. With pytorch cross attention it's about as fast as your patch was.
I don't know how to do this stuff correctly, with the fp8 version on 4080S I get the same gen times as the bf16.
Does Forge Neo supports it? I'm getting an error : NotImplementedError: "LayerNormKernelImpl" not implemented for 'Float8_e4m3fn'. What do I do wrong?
use default on dtype
@Meowzilla What is this option? On main page or in settings?
Forge Neo supports Anima model now (not sure about quants tho)
@MarkinZzZ My bad, I missed the forge part. My thing is for comfy.
@orhay1, Yeah, it seems that Anima_preview works, but not fp8. Anyway OG anima's images in forge neo (at least what I tried to generate) isn't so good though lol. Maybe we need to wait for a proper release, 'cause I just don't like Comfy for its overcomplication and uneven generation
NotImplementedError: "rms_norm" not implemented for 'Float8_e4m3fn'
Looks like we don't have an active mirror for this file right now.
CivArchive is a community-maintained index — we catalog mirrors that volunteers upload to HuggingFace, torrents, and other public hosts. Looks like no one has uploaded a copy of this file yet.
Some files do get recovered over time through contributions. If you're looking for this one, feel free to ask in Discord, or help preserve it if you have a copy.
