Instructions to use InstantX/FLUX.1-dev-Controlnet-Canny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/FLUX.1-dev-Controlnet-Canny with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/FLUX.1-dev-Controlnet-Canny", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
update readme with license, tags an base model
Browse filesit be great to update the license + some additions to the readme that can be nice 😊
README.md
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license:
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# FLUX.1-dev Controlnet
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license: other
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license_name: flux-1-dev-non-commercial-license
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license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
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tags:
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- Text-to-Image
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- ControlNet
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- Diffusers
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- Stable Diffusion
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base_model: black-forest-labs/FLUX.1-dev
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# FLUX.1-dev Controlnet
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