Instructions to use REPA-E/e2e-invae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use REPA-E/e2e-invae 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-invae", 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, links, and structure
#1
by nielsr HF Staff - opened
This PR improves the model card by adding essential metadata, including the pipeline_tag, library_name, and confirming the license. It also structures the content for better readability and adds links to the paper and project page. This enhances the model card's completeness and user experience.
xingjianleng changed pull request status to merged