Instructions to use ThiennNguyen/ControlNet_Finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ThiennNguyen/ControlNet_Finetuning with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("ThiennNguyen/ControlNet_Finetuning") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline
controlnet = ControlNetModel.from_pretrained("ThiennNguyen/ControlNet_Finetuning")
pipe = StableDiffusionControlNetPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", controlnet=controlnet
)controlnet-ThiennNguyen/ControlNet_Finetuning
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning.
You can find some example images below.
prompt: there are some very tall rocks in the desert with trees
prompt: araffe on a cruise ship with a pool and people on deck

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Model tree for ThiennNguyen/ControlNet_Finetuning
Base model
runwayml/stable-diffusion-v1-5