Instructions to use brycegoh/sdxl-cn-example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use brycegoh/sdxl-cn-example with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("brycegoh/sdxl-cn-example") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline
controlnet = ControlNetModel.from_pretrained("brycegoh/sdxl-cn-example")
pipe = StableDiffusionControlNetPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet
)controlnet-brycegoh/sdxl-cn-example
These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning.
You can find some example images below.
prompt: red circle with blue background
prompt: cyan circle with brown floral background

Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
- Downloads last month
- 9
Model tree for brycegoh/sdxl-cn-example
Base model
stabilityai/stable-diffusion-xl-base-1.0