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import gradio as gr
import spaces
from transformers import pipeline
# Initialize Model
get_completion = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", device=0)
@spaces.GPU(duration=120)
def summarize(input: str) -> str:
"""
Summarize the given input text using the sshleifer/distilbart-cnn-12-6 model.
Args:
input (str): The text to be summarized.
Returns:
str: The summarized version of the input text.
"""
output: List[Dict[str, str]] = get_completion(input)
return output[0]['summary_text']
gr.close_all()
####### GRADIO APP #######
title = """<h1 id="title"> Text Summarization </h1>"""
description = """
Summarize any text using the `sshleifer/distilbart-cnn-12-6` model under the hood
- The model used for Summarizing Text [DISTILBART-12-6-CNN](https://huggingface.co/sshleifer/distilbart-cnn-12-6).
"""
css = '''
h1#title {
text-align: center;
}
'''
theme = gr.themes.Soft()
demo = gr.Blocks(css=css, theme=theme)
with demo:
gr.Markdown(title)
gr.Markdown(description)
interface = gr.Interface(fn=summarize,
inputs=[gr.Textbox(label="Text to Summarize", lines=15)],
outputs=[gr.Textbox(label="Result", lines=7)]
)
demo.launch() |