Instructions to use jasperai/Flux.1-dev-Controlnet-Upscaler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jasperai/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("jasperai/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
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- ControlNet
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- super-resolution
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license: cc-by-
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# ⚡ Flux.1-dev: Upscaler ControlNet ⚡
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- ControlNet
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- super-resolution
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- upscaler
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license: cc-by-nc-4.0
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# ⚡ Flux.1-dev: Upscaler ControlNet ⚡
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