Instructions to use XLabs-AI/flux-controlnet-canny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XLabs-AI/flux-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("XLabs-AI/flux-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
- Local Apps Settings
- Draw Things
- DiffusionBee
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This repository provides a checkpoint with trained ControlNet Canny model for
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[FLUX.1-dev model](https://huggingface.co/black-forest-labs/FLUX.1-dev) by Black Forest Labs
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[See our github](https://github.com/XLabs-AI/x-flux-comfyui) for comfy ui workflows.
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# Training details
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This repository provides a checkpoint with trained ControlNet Canny model for
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[FLUX.1-dev model](https://huggingface.co/black-forest-labs/FLUX.1-dev) by Black Forest Labs
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# ComfyUI
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[See our github](https://github.com/XLabs-AI/x-flux-comfyui) for comfy ui workflows.
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# Training details
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