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:
- 3d227e99fc09065c193284b8bcb6ba6a5eae2890c1f71d46a5fbc159cb232745
- Size of remote file:
- 1.39 GB
- SHA256:
- 0b665526282c8bda95ade79affd7ed9e2569da0c1e8327a2ed0d0e162518a6cd
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