Instructions to use jiangdaniel/IClight_i2i with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jiangdaniel/IClight_i2i 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("jiangdaniel/IClight_i2i", 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:
- ba923cd6ab14bf27ae909abab606f85f3763a58debeb6e41cbc86e0a01bfd9c1
- Size of remote file:
- 167 MB
- SHA256:
- b098a5344a351d15c60d5db05875b305c3a79005e144881dfeab9e2670f42ccc
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