Duplicated from jasperai/Flux.1-dev-Controlnet-Upscaler
How to use R1000/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("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("R1000/Flux.1-dev-Controlnet-Upscaler") 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]
https://huggingface.co/R1000/Flux.1-dev-Controlnet-Upscaler/resolve/main/examples/input.jpg
hf download hf://R1000/Flux.1-dev-Controlnet-Upscaler/examples/input.jpg
curl -L -o input.jpg https://huggingface.co/R1000/Flux.1-dev-Controlnet-Upscaler/resolve/main/examples/input.jpg
