Instructions to use REPA-E/e2e-vavae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use REPA-E/e2e-vavae 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-vavae", 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
Improve model card with metadata and links
#1
by nielsr HF Staff - opened
This PR adds missing metadata to the model card, including the pipeline_tag and library_name.
It also adds links to the project page and Github repository for easier access to information and code.
xingjianleng changed pull request status to merged