app.py

import gradio as gr
from transformers import BarkModel, AutoProcessor
import torch
from scipy.io.wavfile import write as write_wav
import os

device = "cpu"
model = BarkModel.from_pretrained("suno/bark-small").to(device)
processor = AutoProcessor.from_pretrained("suno/bark")

def generate_audio(text):
  file_name = "output_file_name.wav"
  inputs = processor(text)
  audio_array = model.generate(**inputs)
  audio_array = audio_array.cpu().numpy().squeeze()
  sample_rate = model.generation_config.sample_rate
  write_wav(file_name,sample_rate,audio_array)
  return file_name


iface = gr.Interface(fn=generate_audio,inputs="text",outputs="audio")
iface.launch()