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import gradio as gr |
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from transformers import pipeline |
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pipe = pipeline("summarization", model="sshleifer/distilbart-xsum-12-3") |
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def main(in_text): |
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print(in_text) |
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answer = pipe(in_text, min_length=5, max_length=20) |
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print(answer) |
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return answer[0]["summary_text"] |
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with gr.Blocks() as demo: |
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gr.Markdown("""# Summarization Engine!""") |
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with gr.Row(): |
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with gr.Column(): |
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text1 = gr.Textbox( |
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label="Input Text", |
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lines=1, |
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) |
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output = gr.Textbox(label="Output Text") |
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b1 = gr.Button("Summarize!") |
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b1.click(main, inputs=[text1], outputs=output) |
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gr.Markdown("""#### powered by *********""") |
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if __name__ == "__main__": |
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demo.launch(debug=True) |
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