Instructions to use Shanav12/CartoonModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shanav12/CartoonModel 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("Shanav12/CartoonModel", 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:
- de89953a41c8dc63c4afe36e3ef1f45320e3b86384a0edf0add1ddebee6b9635
- Size of remote file:
- 4.52 GB
- SHA256:
- 3ea0376dcf065eaefd27806394a90e310001b1a71d4f1cf1f655e86c0e566ffe
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