Instructions to use GreeneryScenery/SheepsControlV4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GreeneryScenery/SheepsControlV4 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/SheepsControlV4", 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
Download diffusion_pytorch_model.bin from GreeneryScenery/SheepsControlV4: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/GreeneryScenery/SheepsControlV4/resolve/e2f80d1b693e44cf5f392cfbdfd2772eca5edbab/diffusion_pytorch_model.bin
- Command line
-
hf download hf://GreeneryScenery/SheepsControlV4@e2f80d1b693e44cf5f392cfbdfd2772eca5edbab/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/GreeneryScenery/SheepsControlV4/resolve/e2f80d1b693e44cf5f392cfbdfd2772eca5edbab/diffusion_pytorch_model.bin
1.46 GB
- Xet hash:
- bc3d28c1e0dcbc358c2ae5f8b540353d0806623b9c30ed475b920238976d0c8b
- Size of remote file:
- 1.46 GB
- SHA256:
- 04cd2114314b5c2753a68d3f280c9b0b126daff79944df1b346c963420abdb15
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