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:
- bfa2ac8a2e8848eb14a10e5da5b90bd783c6958eeef2dd8dc497d53944e805a4
- Size of remote file:
- 1.46 GB
- SHA256:
- 567bca2d679108b04659dd47daef8d04f963fa0e5fed6c21b96226fbd6a4b69b
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