Instructions to use acceptee/DiT4SR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use acceptee/DiT4SR 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("acceptee/DiT4SR", torch_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:
- dfee08bd2f09dbb3e1ad78aee09995526c2521d7ed41fb996170b78459f49585
- Size of remote file:
- 5.2 kB
- SHA256:
- 8b9545113455ef71e763d66d6b04622c9be50cbdc725dae459b8d2b493199af8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.