Instructions to use 24aittl/refine_core with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 24aittl/refine_core 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("24aittl/refine_core", 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:
- 01e7a673a361e9764c0cc8d373e002ac9554e8a4b1f9e9c2e7b58f8af31b1801
- Size of remote file:
- 167 MB
- SHA256:
- 6353737672c94b96174cb590f711eac6edf2fcce5b6e91aa9d73c5adc589ee48
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