Instructions to use RedbeardNZ/Flux.1-dev-Controlnet-Upscaler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RedbeardNZ/Flux.1-dev-Controlnet-Upscaler 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("RedbeardNZ/Flux.1-dev-Controlnet-Upscaler", 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:
- 90cdb8d57a0d9fd969ffdd447798b1f2708a8c831669e1bb35f9f06a1872be82
- Size of remote file:
- 3.58 GB
- SHA256:
- 2a7ea24d2037ff2aa4d25f8b4ce9fe7e739a2cfe6b9d05106788005d5058c8ca
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