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import torchaudio
from audiocraft.models import AudioGen
from audiocraft.data.audio import audio_write
import gradio as gr
model = AudioGen.get_pretrained('facebook/audiogen-medium')
model.set_generation_params(duration=8) # generate 8 seconds.
wav = model.generate_unconditional(1) # generates 4 unconditional audio samples
def AudioGenie(Prompt):
descriptions = [Prompt]
wav = model.generate(descriptions) # generates 3 samples.
for idx, one_wav in enumerate(wav):
# Will save under {idx}.wav, with loudness normalization at -14 db LUFS.
audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)
return wav
gr.Interface(fn=AudioGenie, inputs= 'text', outputs= 'audio').launch(debug=True)
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