Instructions to use molo322/icrelightmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use molo322/icrelightmodel 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("molo322/icrelightmodel", 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:
- 8ac9a4e26b4cd629f3a3bf2748f9f3a39719e7a1ba89f30cc392e73727c07f03
- Size of remote file:
- 246 MB
- SHA256:
- 9706025d0e3053a3cdcc7e6cfa495c5ad951267a29ad08644aadb684ae217e7e
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