Anima-ControlNet-VACE-Depth

A depth ControlNet for Anima, trained with the VACE spaced-block-duplication + zero-conv architecture.

⚠️ This release contains adapter weights only. It is not a standalone model — you must load it together with the Anima base model.


Training

Trained with sd-scripts by kohya-ss

Setting Value
Base Model Anima-Base-V1.0
Optimizer AdamW (fp32 states), weight decay 0.01
Learning rate 5e-5, cosine, 500-step warmup
Effective batch 16
Steps 20,000
Resolution 1024²
Precision bf16 (full_bf16)
Flow shift 5.0 (matches inference)
Loss L2 on flow-matching velocity
Weighting uniform

Tips

  • Depth source: Use DepthAnything V2 for best performance, although this model is trained on a mix of different depth sources, and thus any popular depth preprocessor should in theory work.

Usage

Supported for the moment in ComfyUI through my fork of ComfyUI-Advanced-ControlNet

Credits

  • Anima - Circlestone Labs
  • sd-scripts — kohya-ss.
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