Instructions to use lehduong/OneDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lehduong/OneDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lehduong/OneDiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add model card with paper link, pipeline tag, license, and code link
#1
by nielsr HF Staff - opened
This PR adds a model card to the repository based on the paper One Diffusion to Generate Them All.
It includes:
- A link to the paper.
- The
any-to-anypipeline tag for better discoverability. - The
cc-by-nc-4.0license. - A link to the official Github repository.
- Quickstart installation and inference code
- Qualitative results
- Citation
lehduong changed pull request status to merged