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
Commit History
-
Add metadata and link to paper
Verified signatureHi! 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-image` to ensure the model appears in the correct category on the Hub. - Added `library_name: diffusers` as the configuration indicates compatibility with the diffusers ecosystem. - Linked the model to its [Hugging Face paper page](https://huggingface.co/papers/2603.13089). This metadata helps researchers find and use your work more easily!fe8d8fa
-
Update README.md
Verified signatureb145030 -
Update README.md
Verified signature592ea60
-
Update README.md
Verified signature0e60e6a -
Upload folder using huggingface_hub
Verified signature0a2e8cb -
initial commit
Verified signature3f57d07