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import torch
import gradio as gr
# Use a pipeline as a high-level helper
from transformers import pipeline
text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
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="Project 1: Text Summarizer",
description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")
demo.launch()
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