Instructions to use ghoskno/Color-Canny-Controlnet-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ghoskno/Color-Canny-Controlnet-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ghoskno/Color-Canny-Controlnet-model", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bd50e06211401e7fd387d9e3e0d4512fa1ddc5d0530bfd32f815253fe757ab3
- Size of remote file:
- 723 MB
- SHA256:
- dda1f2c5ac144e826e2fe56771d73e2cb91c8218ae1eafef5120ce4df0611517
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