Instructions to use desimfj/V-Bridge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use desimfj/V-Bridge with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("desimfj/V-Bridge", 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 metadata and link to paper
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team. I'm opening this PR to enhance your model card with standard metadata:
- Added
pipeline_tag: image-to-imageto ensure the model appears in the correct category on the Hub. - Added
library_name: diffusersas the configuration indicates compatibility with the diffusers ecosystem. - Linked the model to its Hugging Face paper page.
This metadata helps researchers find and use your work more easily!