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-10000/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-10000/optimizer.bin
- Command line
-
hf download hf://rgres/Seg2Sat-sd-controlnet@refs/pr/1/v1/checkpoint-10000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rgres/Seg2Sat-sd-controlnet/resolve/refs%2Fpr%2F1/v1/checkpoint-10000/optimizer.bin
2.91 GB
- Xet hash:
- 61ee708bf523f139817737486c78055bad42299fe23ebb77bb526803850625e2
- Size of remote file:
- 2.91 GB
- SHA256:
- 56a73b000cde60261d23e86c4cf5f9c03ca58c615190051547ce456721432214
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