ComfyUI-AnimaFastTrain is an experimental ComfyUI custom node for quickly training in-memory Anima reference context tokens from one or more reference images.
Instead of creating a LoRA, checkpoint, embedding, or safetensors file, AnimaFastTrain learns temporary context tokens during the workflow and injects them into the Anima model’s cross-attention at generation time.
This makes it useful for experiments with character consistency, visual reference influence, and style transfer without writing trained weights to disk.
Main features:
- Trains lightweight reference context tokens directly inside ComfyUI
- Keeps everything in memory, no model files are saved
- Patches the Anima model during sampling
- Supports up to 3 reference images
- Adjustable token count, training steps, learning rate, dtype, and runtime strength
- Useful for quick style/identity experiments before committing to a full LoRA training run
Included nodes:
- AnimaFastTrain - Train Context Tokens
- AnimaFastTrain - Patch Model
Recommended workflow:
Checkpoint Loader -> LoRA Loader -> AnimaFastTrain Patch Model -> KSampler
Train the context tokens from a reference image, patch the final model after other model/LoRA patches, and then generate normally.
Install by cloning the repo or using comfy manager.
GitHub: