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
| license: creativeml-openrail-m | |
| base_model: runwayml/stable-diffusion-v1-5 | |
| tags: | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| - controlnet | |
| inference: true | |
| # controlnet-MadhurGarg/ControlNet_Flowers | |
| These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. | |
| You can find some example images below. | |
| prompt: a flower in black and white | |
|  | |
| prompt: a group of white flowers | |
|  | |
| prompt: a purple flower with green leaves in the background | |
|  | |