Instructions to use sxela/out with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sxela/out with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("sxela/out") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
controlnet-sxela/out
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: anthropomorphic anthropomorphic fat cat as dark vador, lightsaber, star wars, beautiful glowing lights, sci - fi, stunning, intricate, elegant. highly detailed, digital painting. artstation. smooth. sharp focus. illustration. art by artgerm and greg rutkowski and alphonse mucha

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Model tree for sxela/out
Base model
stabilityai/stable-diffusion-xl-base-1.0