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import torchaudio | |
import argparse | |
from stepaudio import StepAudio | |
def main(): | |
parser = argparse.ArgumentParser(description="StepAudio Offline Inference") | |
parser.add_argument( | |
"--model-path", type=str, required=True, help="Base path for model files" | |
) | |
args = parser.parse_args() | |
model = StepAudio( | |
tokenizer_path=f"{args.model_path}/Step-Audio-Tokenizer", | |
tts_path=f"{args.model_path}/Step-Audio-TTS-3B", | |
llm_path=f"{args.model_path}/Step-Audio-Chat", | |
) | |
# example for text input | |
text, audio, sr = model( | |
[{"role": "user", "content": "你好,我是你的朋友,我叫小明,你叫什么名字?"}], | |
"闫雨婷", | |
) | |
torchaudio.save("output/output_e2e_tqta.wav", audio, sr) | |
# example for audio input | |
text, audio, sr = model( | |
[ | |
{ | |
"role": "user", | |
"content": {"type": "audio", "audio": "output/output_e2e_tqta.wav"}, | |
} | |
], | |
"闫雨婷", | |
) | |
torchaudio.save("output/output_e2e_aqta.wav", audio, sr) | |
if __name__ == "__main__": | |
main() | |