Instructions to use MadhurGarg/ControlNet_Flowers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MadhurGarg/ControlNet_Flowers with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("MadhurGarg/ControlNet_Flowers") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 9c834d6eb63481ff301e4284d4816d0c4e61557b82692aa764fc2692f878525e
- Size of remote file:
- 1.45 GB
- SHA256:
- 5dc765658d9de213423f2eff9802eab99ba183c900ffb717d4eb9f8b7de33c80
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.