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Create app.py
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app.py
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import gradio as gr
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import torchaudio
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from audiocraft.models import AudioGen
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from audiocraft.data.audio import audio_write
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model = AudioGen.get_pretrained('facebook/audiogen-medium')
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def infer(prompt):
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model.set_generation_params(duration=5) # generate 5 seconds.
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descriptions = [prompt]
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wav = model.generate(descriptions) # generates 3 samples.
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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(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)
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return "0.wav"
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gr.Interface(
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fn = infer,
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inputs = gr.Textbox(),
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outputs = gr.Audio()
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).launch()
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