Instructions to use BBO66/SounDiT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BBO66/SounDiT with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BBO66/SounDiT", torch_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
Update model card with metadata, links, and description
#1
by nielsr HF Staff - opened
Hi, I'm Niels from the Hugging Face community science team. I've updated your model card to include important metadata and links to your research artifacts.
Specifically, this PR:
- Adds the
diffuserslibrary name andotherpipeline tag to the metadata. - Links to the SounDiT paper, the project page, and the source code.
- Adds a short description of the Geo-contextual Soundscape-to-Landscape (GeoS2L) task.
- Includes setup and usage instructions from your GitHub README.
- Adds the BibTeX citation.
This will help users discover, use, and cite your model more easily!
BBO66 changed pull request status to merged