Instructions to use karoldobiczek/sam-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use karoldobiczek/sam-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("karoldobiczek/sam-controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3a3a4dd167fb0109e2ed0293e9dc1751035d05cf28781388f91c5266d3e8a80e
- Size of remote file:
- 1.45 GB
- SHA256:
- 9deba0210d46804829cb14034ac1f3edbba1abb3c96508d62bce585f2c92809f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.