Instructions to use hf-internal-testing/tiny-AudioLDM2Pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-AudioLDM2Pipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-AudioLDM2Pipeline", 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:
- 03fbc49e11146a4b8fe58f117fc1972e47cacb13df28ede79b05cd22d894bca6
- Size of remote file:
- 4.07 kB
- SHA256:
- c757262eec917164ee2ce09dbe698438c2ec00d3eef309bb5daf17bec8e2de92
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