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 Settings
- Draw Things
- DiffusionBee
Download v1/checkpoint-8000/optimizer.bin from rgres/Seg2Sat-sd-controlnet: direct link, hf CLI and curl.
- Browser
- Download file 2.91 GB
-
https://huggingface.co/rgres/Seg2Sat-sd-controlnet/resolve/refs%2Fpr%2F1/v1/checkpoint-8000/optimizer.bin
- Command line
-
hf download hf://rgres/Seg2Sat-sd-controlnet@refs/pr/1/v1/checkpoint-8000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rgres/Seg2Sat-sd-controlnet/resolve/refs%2Fpr%2F1/v1/checkpoint-8000/optimizer.bin
2.91 GB
- Xet hash:
- 5d9fde99068e46066d75c1944cde0fb30f49a6e94bd4c2665c7c13844752b5ee
- Size of remote file:
- 2.91 GB
- SHA256:
- dd1c206c2a6a1b2c1cb45096709f2e0f96b0f9864e8fa87102b90ce254eda2c9
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