Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
Instructions to use rgres/Seg2Sat-sd-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rgres/Seg2Sat-sd-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("rgres/Seg2Sat-sd-controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| license: creativeml-openrail-m | |
| base_model: stabilityai/stable-diffusion-2-1-base | |
| tags: | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| - controlnet | |
| inference: true | |
| # rgres/Seg2Sat-sd-controlnet | |
| These are controlnet weights trained on stabilityai/stable-diffusion-2-1-base with new type of conditioning. | |