Instructions to use GreeneryScenery/SheepsControlV7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GreeneryScenery/SheepsControlV7 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/SheepsControlV7", 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 checkpoint-5000/optimizer.bin from GreeneryScenery/SheepsControlV7: direct link, hf CLI and curl.
- Browser
- Download file 2.91 GB
-
https://huggingface.co/GreeneryScenery/SheepsControlV7/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://GreeneryScenery/SheepsControlV7/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/GreeneryScenery/SheepsControlV7/resolve/main/checkpoint-5000/optimizer.bin
2.91 GB
- Xet hash:
- 8847db3941d664be2fd6ce7d22d9b482ba19fa2c3582bee3a2e624f038c8524d
- Size of remote file:
- 2.91 GB
- SHA256:
- 4473be63e71bc3847955e970b780a41e4c11e6408afdf97d95717f1bde736cd6
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