Instructions to use sohith18/controlnet-satellite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sohith18/controlnet-satellite with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sohith18/controlnet-satellite", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download checkpoint-6300/optimizer.bin from sohith18/controlnet-satellite: direct link, hf CLI and curl.
- Browser
- Download file 2.89 GB
-
https://huggingface.co/sohith18/controlnet-satellite/resolve/main/checkpoint-6300/optimizer.bin
- Command line
-
hf download hf://sohith18/controlnet-satellite/checkpoint-6300/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/sohith18/controlnet-satellite/resolve/main/checkpoint-6300/optimizer.bin
2.89 GB
- Xet hash:
- 4f30d77a88e0c7048030e27635df86fde8ac9f1ea9f43454fc3ab91f92174c5d
- Size of remote file:
- 2.89 GB
- SHA256:
- ba40e62f4f190aa715e16e89a0e4330cc60577bf8d36e0fc9dd4eec55d6bedbb
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