import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("alppo/amuse", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
This is a conditional unet model designed for music generation using mel spectrogram images. The model was trained on the alppo/music dataset, which includes 5 different genres. It accepts 512x512 images and 1x64 condition embeddings, which can be generated from my own variational autoencoder implementation.
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