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import torch
import gradio as gr
from transformers import pipeline
# Use a pipeline as a high-level helper
device = 0 if torch.cuda.is_available() else -1
text_summary = pipeline("summarization", model="Falconsai/text_summarization",device=device,torch_dtype=torch.bfloat16)
def summary(input):
output = text_summary(input)
return output[0]['summary_text']
gr.close_all()
# Create the Gradio interface
demo = gr.Interface(
fn=summary,
inputs=[gr.Textbox(label="INPUT THE PASSAGE TO SUMMARIZE", lines=10)],
outputs=[gr.Textbox(label="SUMMARIZED TEXT", lines=4)],
title="PAVISHINI @ GenAI Project 1: Text Summarizer",
description="This application is used to summarize the text"
)
demo.launch()
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