App.py

import torch
import gradio as gr

# Use a pipeline as a high-level helper
from transformers import pipeline 

#model_path = ("../Models/models--sshleifer--distilbart-cnn-12-6/snapshots/a4f8f3ea906ed274767e9906dbaede7531d660ff")

text_summary = pipeline("summarization", model= model_path,

                        torch_dtype=torch.bfloat16)

#text= ''''''

#print(text_summary(text));

def summary (input):
    output = text_summary(input)
    return output[0]['summary_text']

gr.close_all()

# demo = gr.Interface(fn=summary, inputs="text",outputs="text")
demo = gr.Interface(fn=summary,
                    inputs=[gr.Textbox(label="Input text to summarize",lines=6)],
                    outputs=[gr.Textbox(label="Summarized text",lines=4)],
                    title="@GenAILearniverse Project 1: Text Summarizer",
                    description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")
demo.launch()