Instructions to use jdp8/audioldm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdp8/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("jdp8/audioldm2", 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
- Xet hash:
- 9fb115efa8fc0523ecb41a42f2baa9248b296f4dee9bcc88ec96da18f62e283c
- Size of remote file:
- 222 MB
- SHA256:
- b3494aadd9cf3e3f0cbb4e913f9b35a25da4a3cb709852e204b667ae5890f758
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