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#!pip install -q torch transformers gradio | |
import os | |
import io | |
from transformers import pipeline | |
import gradio as gr | |
get_completion = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6") | |
def summarize(input): | |
output = get_completion(input) #takes an input | |
return output[0]['summary_text'] #returns an output as summarized text | |
gr.close_all() | |
#create an interface in Gradio | |
demo = gr.Interface(fn=summarize, #mentioning the function | |
inputs=[gr.Textbox(label="Text to summarize", lines=6)], #input interface Textbox | |
outputs=[gr.Textbox(label="Result", lines=3)], | |
title="Text summarization with distilbart-cnn", | |
description="Summarize any text using the `sshleifer/distilbart-cnn-12-6` model under the hood!" | |
) | |
demo.launch() #to luanch an app. share=True it creates a global link which can be used to access it without a localhost | |