Instructions to use laidawang/test_flux_controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use laidawang/test_flux_controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("laidawang/test_flux_controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "black-forest-labs/FLUX.1-dev", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- f32250aebe14802baddfd4dd89296fce3a4c27ea2c2aad9588343efad492c580
- Size of remote file:
- 2.33 MB
- SHA256:
- 18fc272055296d86d7768dc4c3b53000dfdbe683e5ed0cb89750216fa7c6717f
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