Instructions to use jasperai/Flux.1-dev-Controlnet-Surface-Normals with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jasperai/Flux.1-dev-Controlnet-Surface-Normals 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-Surface-Normals", 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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# ⚡ Flux.1-dev: Surface Normals ControlNet ⚡
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This is [Flux.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) ControlNet for Surface Normals map
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<img style="width:700px;" src="examples/showcase.jpg">
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# ⚡ Flux.1-dev: Surface Normals ControlNet ⚡
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This is [Flux.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) ControlNet for Surface Normals map developed by Jasper research team.
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<img style="width:700px;" src="examples/showcase.jpg">
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