Instructions to use ShambaC/SAR-Intruct-Pix2Pix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShambaC/SAR-Intruct-Pix2Pix 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("ShambaC/SAR-Intruct-Pix2Pix", 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:
- 75d6efabb8326fc94bc17509a25f1292b18dd3550265d5c68a523078c3de25f0
- Size of remote file:
- 6.88 GB
- SHA256:
- 9a3364caf0f0e4b70961f32d796833129adc153bf3c8534f4b067fb6f7f90fba
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