Instructions to use cvssp/audioldm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cvssp/audioldm2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cvssp/audioldm2", 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
- Xet hash:
- 73b96230aa2f80caada0fbbe5ce1b0c50d8d14d41bb6d7566305bfc192fdddc1
- Size of remote file:
- 1.36 GB
- SHA256:
- c1d0c8f1c739db9343c12ea4b0e3f2c97a833b3c072c251e91d97b7326fefb4e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.