Instructions to use GreeneryScenery/SheepsControlV9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GreeneryScenery/SheepsControlV9 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/SheepsControlV9", 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:
- a0cb0ada0cf0fc85b70c8b0185705f975fee695b37f6730bcb3f2b4e8a9af109
- Size of remote file:
- 1.46 GB
- SHA256:
- f22c31b12e04054d8e3c8963b713517dfc58eef20b452239507ff57dec2b8c20
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