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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() |