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:
- 78b968f73e2ec5c28c56b0895cc45062a91baaffad3a053a2ab1f663042e2b16
- Size of remote file:
- 246 MB
- SHA256:
- 3ec1127f69cbb71d8fadbba1e4200c07a563fe9152a20ea90442fb6d8e3cb28f
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