app.py

from transformers import pipeline
import gradio as gr
import numpy as np

pipe = pipeline(model="openai/whisper-tiny")

def asr(test_file):        
    return pipe(test_file, max_new_tokens=100) 

def gradio_asr(test_file):
    return asr(test_file)

asr_upload = gr.Interface(fn=gradio_asr,
                   inputs=gr.Audio(source='upload', type='filepath'),
                   outputs='text')

app_mic = gr.Interface(fn=gradio_asr,
                   inputs=gr.Audio(source='microphone', type='filepath'),
                   outputs='text')

app = gr.TabbedInterface([asr_upload, app_mic], ["语音文件", "实时识别"])
app.launch(server_name='0.0.0.0', ssl_verify=False)