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", 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:
- 2892d94c8a823d32034c7cabf9157ec522cb4cf27b9e312af5892a0fd247606d
- Size of remote file:
- 4.74 MB
- SHA256:
- cfb555ca6f1d76278436c48bafea78b5122b9496434694cb8866c096fb1c6ad0
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