Instructions to use fishze/Refacade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fishze/Refacade with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fishze/Refacade", 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 license, pipeline tag, and library name to metadata
#2
by nielsr HF Staff - opened
This PR enriches the model card's metadata by adding:
license: apache-2.0pipeline_tag: image-to-image, which will allow the model to be discovered under theimage-to-imagepipeline on the Hub.library_name: diffusers, which enables the automated "how to use" widget, as the model is built upon Diffusers.
No changes are made to the existing markdown content, as it is already comprehensive.
Please review and merge this PR if everything looks good.
fishze changed pull request status to merged
Thanks!