---
license: mit
---
Thanks for Tencent release the controlenet training code, so Just a test version for Hunyuan tile model. More test is on going. join my personal qq group 294060503 for more discussion

Please follow https://github.com/Tencent/HunyuanDiT/blob/main/controlnet/README.md to run the model.

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/641edd91eefe94aff6de024c/928OhsRzsu7azmoWLGUXx.jpeg)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/641edd91eefe94aff6de024c/yQ9PSkdpP9hss8Y4CXwAO.png)

remember modify the ./hydit/config.py change the line 50 to 
    parser.add_argument("--control-type", type=str, default='canny', choices=['canny', 'depth', 'pose', 'tile'], help="Controlnet condition type")

Inference example
You can use the following command line for inference.

Using tile ControlNet during inference
python3 sample_controlnet.py  --no-enhance --load-key ema --infer-steps 100 --control-type tile --prompt "input your prompt here" --condition-image-path controlnet/asset/input/yourimg.jpg --control-weight 1.0