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Anima ControlNet VACE Depth

circlestone-labs-non-commercial-license

ArtOtherBasismodellAnima-Base-V1.0VersionRevision 4ffaa3cCBewertung

Modellquelle

Art
Other
Dateigröße
568 MB
Basismodell
Anima-Base-V1.0
Version
vRevision 4ffaa3c
Aktualisiert
7. Okt. 2026
Downloads
0
Quelle
Hugging Face

Quellenbeschreibung

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

SettingValue
Base ModelAnima-Base-V1.0
OptimizerAdamW (fp32 states), weight decay 0.01
Learning rate5e-5, cosine, 500-step warmup
Effective batch16
Steps20,000
Resolution10242
Precisionbf16 (full_bf16)
Flow shift5.0 (matches inference)
LossL2 on flow-matching velocity
Weightinguniform

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.

Quellen

1 Quelle
Hugging FacePrimärVersion 4ffaa3cf5854d5eac5b13447e043d2a8ff2cc4e7
huggingface.co/TaihoC/Anima-ControlNet-VACE-Depth/tree/4ffaa3cf5854d5eac5b13447e043d2a8ff2cc4e7

Verifiziert 7. Okt.

Modellartefakte

1 Artefakt

anima-vace-depth.safetensors

safetensors · 568 MB · SHA-256 29762e7037bd…802d · Hugging Face

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Quellenauszüge

3 Auszüge

--- license: other license_name: circlestone-labs-non-commercial-license base_model: Anima-Base-V1.0 tags: - text-to-image - controlnet - depth - anima pipeline_tag: text-to-image --- # 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](https://github.com/TaihoC/ComfyUI-Advanced-ControlNet-Anima/tree/feat/anima-vace-controlnet) ## Credits - **Anima** - Circlestone Labs - **sd-scripts** — kohya-ss.

Source context: 0 downloads · 16 likes · Pipeline text-to-image · Repo TaihoC/Anima-ControlNet-VACE-Depth

Source context: 0 downloads · 12 likes · Pipeline text-to-image · Repo TaihoC/Anima-ControlNet-VACE-Depth