app.py

import gradio as gr
from gradio.mix import Parallel


title = 'Comparing different dialogue summarization models'
description = 'Here we are going to compare different summarization model namely BART-LARGE model which is trained on samsum data and t5small model which is also trained on the same dataset.'

example = [[''' A: Hello B. How are you?
B: I'm good. How's your course going on these days?
A: It's going well. Pretty tiring but overall fun.
B: That's great to hear. If you are free wanna grab a cup of coffee?
A: Sure!!!! I recently discovered a new cafe near my home.
B: Awesome. Let's go.'''],
['''Rohit: Hi, how’re you?
Mahesh: I’m fine. What about you?
Rohit: Good. How’s your work going on?
Mahesh: Not great.
Rohit: Why? What happened?
Mahesh: My workplace is far from my home. Most of my time is spent commuting and I'm not able to give time to my family.
Rohit: Oh!! That sounds taxing. What are you planning to do now?
Mahesh: I will again start applying for jobs near my home.
Rohit: Best of luck man!!''']]

model1 = gr.Interface.load("huggingface/philschmid/bart-large-cnn-samsum",
                            title = 'BART-Large-cnn-samsum',
                            description = 'This is a pre trained model'
                            )

model2 = gr.Interface.load("huggingface/anegi/t5smallmodel",
                            title = 'T5-small model',
                            description = 'This is a self trained model',
                            )


Parallel(model1, model2 ,
         title = title,
         description = description,
         inputs = gr.inputs.Textbox(lines = 7, label = 'Input Text', placeholder = 'Please enter your dialogue text here'),
         layout='vertically',
         examples = example,
         theme = 'peach' ).launch()