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:
- 84ffe9ffd9ee6789053583c0eb3fd3c6c10c97890313aa872d083eb26a9d02a8
- Size of remote file:
- 2.91 GB
- SHA256:
- c1c869b29dbbb876ec4184bd791d186201a6996f697ea6f4186cb7edc1645d72
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