(repo_id, torch_dtype=torch.float16)
>>> pipe = pipe.to("cuda")

>>> prompt = "Techno music with a strong, upbeat tempo and high melodic riffs"
>>> audio = pipe(prompt, num_inference_steps=10, audio_length_in_s=5.0).audios[0]

>>> # save the audio sample as a .wav file
>>> scipy.io.wavfile.write("techno.wav", rate=16000, data=audio)  AudioPipelineOutput  class diffusers.AudioPipelineOutput  < source > ( audios: ndarray  )   Parameters   audios 