Instructions to use khanghy1000/Anima-ControlNet-VACE-Canny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusion Single File
How to use khanghy1000/Anima-ControlNet-VACE-Canny with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| license: other | |
| license_name: circlestone-labs-non-commercial-license | |
| license_link: LICENSE.md | |
| base_model: | |
| - circlestone-labs/Anima | |
| base_model_relation: adapter | |
| tags: | |
| - controlnet | |
| - canny | |
| - anima | |
| - text-to-image | |
| - diffusion-single-file | |
| - comfyui | |
| datasets: | |
| - RicemanT/booru-essence-2026 | |
| ## Anima-ControlNet-VACE-Canny | |
| A Canny ControlNet for [Anima](https://huggingface.co/circlestone-labs/Anima), trained with [Anima VACE ControlNet implementation by TaihoC](https://github.com/TaihoC/sd-scripts-animaCN/tree/feat/anima-vace-controlnet). | |
| ⚠️ Requires the `fix/anima-vace-hardening` branch of [PineCookie/ComfyUI-Advanced-ControlNet](https://github.com/PineCookie/ComfyUI-Advanced-ControlNet/tree/fix/anima-vace-hardening). (TaihoC's fork currently has a duplicate control hook bug.) | |
|  | |
| --- | |
| ## Training Details | |
| ### Dataset | |
| - **Dataset**: ~15,000 Danbooru images from [RicemanT/booru-essence-2026](https://huggingface.co/datasets/RicemanT/booru-essence-2026). | |
| - **Canny Edge Maps**: Generated using `cv2.Canny` with `min_threshold=100` and `max_threshold=200` (no random thresholds). | |
| - **Caption Dropout**: 10%. | |
| ### Hyperparameters | |
| - **Control Blocks**: 4 control blocks, connected to the base model at blocks 0, 7, 14, and 21. | |
| - **Batch Size**: 16 (GPU: 2, Gradient Accumulation: 8) | |
| - **Training Steps**: 3000 | |
| - **Learning Rate**: 5e-5, cosine, 150 warmup steps | |
| - **Optimizer**: `AdamW_adv` | |
| - betas: (0.9, 0.99) | |
| - use_atan2: True | |
| - orthogonal_gradient: iterative | |
| - state_precision: bf16_sr | |
| - stochastic_rounding: True | |
| - **Training Precision**: full bf16 | |
| - **Timestep Sampling**: `shift`, `discrete_flow_shift=3.0`, `sigmoid_scale=1.0` | |
| - **Resolution**: 1024x1024 | |
| **Peak VRAM Usage**: ~32GB (no gradient checkpointing) | |
| **Compute Cost**: ~10 hours on 1x L40S | |
| --- | |
| ### Credits | |
| - [Anima VACE ControlNet - TaihoC](https://github.com/TaihoC/sd-scripts-animaCN/tree/feat/anima-vace-controlnet) | |
| - [booru-essence-2026 - RicemanT](https://huggingface.co/datasets/RicemanT/booru-essence-2026) | |
| - [sd-scripts - kohya-ss](https://github.com/kohya-ss/sd-scripts) | |
| - [Anima - Circlestone Labs](https://huggingface.co/circlestone-labs/Anima) | |