Create README.md

README.md

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+---
+license: other
+license_name: circlestone-labs-non-commercial-license 
+base_model: Anima-Base-V1.0
+tags:
+  - text-to-image
+  - controlnet
+  - depth
+  - anima
+  - cosmos-predict2
+  - vace
+  - comfyui
+  - sd-scripts
+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.
+
+## Credits
+
+- **Anima** - Circlestone Labs
+- **sd-scripts** — kohya-ss.
+