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:
- 9baf50e6fd7e4e8e64bd2602d61dcc864f746c3f0a8c0387e7a58edd8a8a0bed
- Size of remote file:
- 31.2 kB
- SHA256:
- 16f18ebd44525ca11285b4a926e4cec311defd91a86911c7d9909fc1e1f3fa9d
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