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This is a general finetuned + distilled model. Better prompt adherence, stability, details, lighting, and LoRA compatibility. No bias, no overfitted default style. And 4x faster.
Source du modèle
Description de la source
RDBT [Anima]
This is a general finetuned + distilled model. Better prompt adherence, stability, details, lighting, and LoRA compatibility. No bias, no overfitted default style. And 4x faster.
Dataset contains ~10k images high quality images with accurate anatomy. Does not contain any shiny plastic glossy AI image. (Training AI with AI images only makes it slopper.) I handpicked every single image.
See this page for update log and version info.
For advanced users: The RDBT model is trained as LoRA natively. See this page for original LoRA.
Sharing merges using this model is not allowed. This "restriction" won't affect anyone. It's only aimed at those who steal others' models to sell. If someone is selling this model as their own, I'm happy to list them here so everyone knows.
Sources
1 sourceArtefacts du modèle
1 artefactrdbtAnima_p3V024f16StepDmd2.safetensors
safetensors · fp16 · full · 3,89 GB · SHA-256 6bb0aca7a086…59de
Extraits de sources
3 extraitsSource context: 19767 downloads · Type Checkpoint · Base model Anima
Known model thieves : NukeA.I (selling this model behind paywall on tensorart).
I wrote a story about it. Also contains a guide for trainers about "how to bake special trigger word into your model".
Usage:
Recipe : This model + style LoRA you want, normally you can go LoRA strength 1 without issues (unless the style LoRA is super overfitted)
Settings:
CFG: 1~3. This model has been distilled. You can disable CFG (CFG 1) and 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.
Steps: 16+ (some versions can be 8)
Prompt:
Always specify style in prompt . Otherwise, you will get random/mixed style. This is a feature, not a bug. This model does NOT have overfitted default style (which ignores prompt and is always active).
Quality tags:
Omit ALL quality tags. You don't need those. 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.
Misc.
Base model:
prefix with ym : AnimaYume ( hf link ) ( civitai link ).
prefix with b,p : Anima pretrained ( hf link )
Source context: 18194 downloads · Type Checkpoint · Base model Anima
Source context: 17782 downloads · Type Checkpoint · Base model Anima
