Image-to-Image
Diffusers
PyTorch
Safetensors
English
StableDiffusionInpaintPipeline
stable-diffusion
image-inpainting
remote-sensing
satellite
vhr
diffusion
geospatial
Instructions to use kaopanboonyuen/KAO-DIFFSAT-VHR-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kaopanboonyuen/KAO-DIFFSAT-VHR-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kaopanboonyuen/KAO-DIFFSAT-VHR-v1", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 25bbd942c9c9f477d64468494f65a9c7bd5a197c85c43d982beddd329c1aecfd
- Size of remote file:
- 2.36 MB
- SHA256:
- dc9e38b56235159316bee1dd1bce71521d0a4c8f279f8edd4c962db95e879e80
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