Instructions to use REPA-E/e2e-sdvae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use REPA-E/e2e-sdvae 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("REPA-E/e2e-sdvae", 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:
- ccc156b2443c5dc1f0d5ce93d7de43cb95bd44d787f9746d8c106ab9d08e4edc
- Size of remote file:
- 11.1 MB
- SHA256:
- c39ae9083d251454180f195b2dc39b1bf2becfcea65794626daffc400e5d3905
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