Instructions to use GreeneryScenery/SheepsControlV8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GreeneryScenery/SheepsControlV8 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("GreeneryScenery/SheepsControlV8", 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:
- 884c7a654ad8143fecad02cf40f8476a53ff5dd81a7df911913e22ec5962138f
- Size of remote file:
- 2.91 GB
- SHA256:
- b1932e4a6a3a278f7cae5d60f57f73cfc3d7e81f7b63a71e2a4ca70afca9df3c
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