app.py

import gradio as gr
from transformers import pipeline

summarizer = pipeline("summarization")

def summarize(text):
  return summarizer(text, max_length=400, min_length=50)[0]['summary_text']
 
  
title = "Music Spleeter"
description = "Clearing a musical composition of the performer's voice is a common task. It is solved well, for example, by professional audio file editing programs. AI algorithms have also been gaining ground recently."
article = "<div style='text-align: center; max-width:800px; margin:10px auto;'><p>In this case we use Deezer's Spleeter with ready pretrained models. It can leave as an output both just the music and just the performer's voice.</p><p>Sources: <a href='https://github.com/deezer/spleeter/' target='_blank'>Spleeter</a>: a Fast and Efficient Music Source Separation Tool with Pre-Trained Models</p><p style='text-align: center'><a href='https://starstat.yt/cat/music' target='_blank'>StarStat Music</a>: Youtubers Net Worth in category Music</p></div>"
    
gr.Interface(fn=summarize, inputs=gr.inputs.Textbox(lines=7, placeholder="Enter text to summarize here"), outputs="text", title=title, description=description, article=article).launch()