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:
- 948995c6d93326e874efdd3224957fb399a94fd978e953c3b3821951bfce7014
- Size of remote file:
- 723 MB
- SHA256:
- 2b75d3d46f945051a061900947bab0d0eedcc029355316839477d20d64e11bb8
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