Music Analysis
Collection
3 items • Updated • 1
Diffusers
Safetensors
PyTorch
AudioDiffusionPipeline
unconditional-audio-generation
diffusion-models-class
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("SeyedAli/audio-diffusion-electronic", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Unconditional music audio generation 🧨
This model is a diffusion model for unconditional audio generation of music in the genre Electronic
Usage
from IPython.display import Audio
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("SeyedAli/audio-diffusion-electronic")
output = pipe()
display(output.images[0])
display(Audio(output.audios[0], rate=pipe.mel.get_sample_rate()))
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