Instructions to use H-oliday/SwiftVR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use H-oliday/SwiftVR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("H-oliday/SwiftVR", 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 pipeline tag, library name and metadata
#1
by nielsr HF Staff - opened
Hi! This PR adds relevant metadata to the model card:
pipeline_tag: image-to-image: This ensures the model is correctly categorized for video and image restoration tasks.library_name: diffusers: The providedconfig.jsonand checkpoint layout indicate compatibility with the Diffusers library format.- It also maintains the existing license and improves the content structure by adding a citation section.
These changes help in making the model more discoverable and usable on the Hugging Face Hub.