Instructions to use GraydientPlatformAPI/juggapaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/juggapaint 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("GraydientPlatformAPI/juggapaint", 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:
- 24b25cb32eb47c07a9c60515c94f037682fa9ed706810d92df37a3311be793e2
- Size of remote file:
- 246 MB
- SHA256:
- 85a7a083279150e9ac4f4f8482052253110a95fc0e3f530d65ceb591df43ee5e
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