The model can also produce nonverbal communications like laughing, sighing and crying.
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Adding non-speech cues to the input text
inputs = processor("Hello uh  [clears throat], my dog is cute [laughter]")
audio_array = model.generate(**inputs)
audio_array = audio_array.cpu().numpy().squeeze()

To save the audio, simply take the sample rate from the model config and some scipy utility:
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