Instructions to use mit-han-lab/nunchaku-flux.1-canny-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mit-han-lab/nunchaku-flux.1-canny-dev 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("mit-han-lab/nunchaku-flux.1-canny-dev", 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:
- 8f2f77cf4284422b52da99829e795a51f9c8a978cc525ad23b155b5e8503609d
- Size of remote file:
- 7.04 GB
- SHA256:
- 70790956e00af45b4c21a88083673578f131d8fa3c01dc50978cea21c80cf3c5
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