39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
import torchaudio
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import time
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from audiocraft.models.musicgen import MusicGen
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from audiocraft.data.audio import audio_write
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MODEL_NAME = "facebook/musicgen-large"
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MUSIC_DURATION_SECONDS = 60
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print("obtaining model...")
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model = MusicGen.get_pretrained(MODEL_NAME)
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model.set_generation_params(duration=MUSIC_DURATION_SECONDS)
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descriptions = [
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"gentle, calming lo-fi beats that helps with studying and focusing",
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"calm, piano lo-fi beats to help with studying and focusing",
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"gentle lo-fi hip-hop to relax to",
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"gentle, quiet synthwave lo-fi beats",
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"morning lo-fi beats",
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]
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print("model obtained. generating audio...")
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a = time.time()
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wav = model.generate(descriptions)
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b = time.time()
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print(f"audio generated. took {b - a} seconds.")
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for idx, one_wav in enumerate(wav):
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# Will save under {idx}.wav, with loudness normalization at -14 db LUFS.
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audio_write(
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f"{idx}",
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one_wav.cpu(),
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model.sample_rate,
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format="mp3",
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strategy="loudness",
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loudness_compressor=True,
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)
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