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
Download 4.jpg from ghoskno/Color-Canny-Controlnet-model: direct link, hf CLI and curl.
- Browser
- Download file 1.38 MB
-
https://huggingface.co/ghoskno/Color-Canny-Controlnet-model/resolve/main/4.jpg
- Command line
-
hf download hf://ghoskno/Color-Canny-Controlnet-model/4.jpg
-
curl -L -o 4.jpg https://huggingface.co/ghoskno/Color-Canny-Controlnet-model/resolve/main/4.jpg
1.38 MB

- Xet hash:
- 77f6da7dd414babda28959408f46da992d2ed324c5540c808891c768073f9ad5
- Size of remote file:
- 1.38 MB
- SHA256:
- 899db1c510285d89f7f74cf68797ea355da61e1cd9962485bdc3adad576d450e
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