app.py

from transformers import PegasusForConditionalGeneration,PegasusTokenizer
import gradio as grad



mdl_name = "google/pegasus-xsum"

pegasus_tkn = PegasusTokenizer.from_pretrained(mdl_name)

mdl = PegasusForConditionalGeneration.from_pretrained(mdl_name)



def summarize(text):
    
    tokens = pegasus_tkn(text, 
                         truncation = True,
                         padding="longest", 
                         return_tensors="pt")
    
    txt_summary = mdl.generate(**tokens)
    
    response = pegasus_tkn.batch_decode(txt_summary, 
                                        skip_special_tokens=True)
    
    return response

    
txt = grad.Textbox(lines = 10,
                   label = "English",
                   placeholder = "English Text here")

out = grad.Textbox(lines = 10, 
                   label = "Summary")

grad.Interface(summarize, 
               inputs = txt, 
               outputs = out).launch()