maestro-150k

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README(From Huggingface)

Dance Diffusion is now available in 🧨 Diffusers.

FP32

# !pip install diffusers[torch] accelerate scipy
from diffusers import DiffusionPipeline
from scipy.io.wavfile import write

model_id = "harmonai/maestro-150k"
pipe = DiffusionPipeline.from_pretrained(model_id)
pipe = pipe

audios = pipe(audio_length_in_s=4.0).audios

# To save locally
for i, audio in enumerate(audios):
    write(f"maestro_test_{i}.wav", pipe.unet.sample_rate, audio.transpose())
    
# To dislay in google colab
import IPython.display as ipd
for audio in audios:
    display(ipd.Audio(audio, rate=pipe.unet.sample_rate))

FP16

Faster at a small loss of quality

# !pip install diffusers[torch] accelerate scipy
from diffusers import DiffusionPipeline
from scipy.io.wavfile import write
import paddle

model_id = "harmonai/maestro-150k"
pipe = DiffusionPipeline.from_pretrained(model_id, dtype=paddle.float16)
pipe = pipe

audios = pipeline(audio_length_in_s=4.0).audios

# To save locally
for i, audio in enumerate(audios):
    write(f"maestro_test_{i}.wav", pipe.unet.sample_rate, audio.transpose())
    
# To dislay in google colab
import IPython.display as ipd
for audio in audios:
    display(ipd.Audio(audio, rate=pipe.unet.sample_rate))

Model Files

• README.md (1.3 KB)

• model_index.json (202.0 B)

• scheduler/scheduler_config.json (108.0 B)

• unet/config.json (1.2 KB)

• unet/model_state.pdparams (844.6 MB)

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