Diffusers
Safetensors
PyTorch
AudioDiffusionPipeline
unconditional-audio-generation
diffusion-models-class
Instructions to use Skier8402/audio-diffusion-punk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Skier8402/audio-diffusion-punk with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Skier8402/audio-diffusion-punk", 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:
- dfd2db1bc99a6ca1dcb55c3307f7af123806f9b2e2e0f744d1b925ad7a74f2f7
- Size of remote file:
- 455 MB
- SHA256:
- 421fe5c790f4b123e93e2234131e517b387dd11b634fb1a3d7f3e877d722967d
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