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| import gradio as gr | |
| from gradio.mix import Parallel | |
| description = 'Dialogue summarization models' | |
| title = 'Comparing different dialogue summarization models' | |
| example = [['''A : Hello man. How are you? | |
| B: I'm good. How's your course going these days? | |
| A: Its going well. Pretty tiring byt overall fun. | |
| B: That's great to hear. Wanna grab a cup of coffee? | |
| A: Sure! I recently discovered a new cafe near my home. | |
| B: Awesome. Let's go.''']] | |
| model1 = gr.Interface.load("huggingface/philschmid/bart-large-cnn-samsum", | |
| title = 'BART-Large-cnn-samsum' | |
| ) | |
| model2 = gr.Interface.load("huggingface/anegi/t5smallmodel", | |
| title = 'T5-small model', | |
| ) | |
| Parallel(model1, model2 , | |
| title = title, | |
| inputs = gr.inputs.Textbox(lines = 7, label = 'Input Text', placeholder = 'Please enter your dialogue text here'), | |
| outputs= gr.outputs.Textbox(type="auto",label='Summary generated by the model'), | |
| example = example, | |
| theme = 'dark-peach' ).launch() | |