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import gradio as gr | |
from gradio import inputs | |
from gradio.mix import Parallel | |
description = 'Dialogue summarization models' | |
title = 'Comparing different dialogue summarization models' | |
example = [['''Aakash: Do you watched last night match? | |
Vikas: No, I was busy. What happended? | |
Aakash: Barcelona won their game against Sevilla 1-0. Pedri scored an sensational goal. | |
Vikas: Oh really!!! I have to watch the highlights at home. | |
Aakash: Yes, I am so excited for the new upcoming season. Xavi really doing wonders. | |
Vikas: Exactly!! Xavi has changed the way Barcelona play. The good days are coming back. ''']] | |
io1 = gr.Interface.load("huggingface/anegi/t5smallmodel", | |
title='Dialogue Summarization using t5-small model', | |
inputs = [ | |
gr.inputs.Textbox(lines = 7, label = 'Text', placeholder = 'Enter your text here: ') | |
], | |
description='This is a self-trained model', | |
example = example | |
) | |
io2 = gr.Interface.load("huggingface/philschmid/bart-large-cnn-samsum", | |
title='Dialogue Summarization using bart large cnn', | |
description='This is a pre trained model ' | |
) | |
Parallel(io1,io2).launch() |