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import torch |
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import gradio as gr |
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from transformers import pipeline |
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text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16) |
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def summary (input): |
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output = text_summary(input) |
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return output[0]['summary_text'] |
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gr.close_all() |
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demo = gr.Interface(fn=summary, |
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inputs=[gr.Textbox(label="Input text to summarize",lines=6)], |
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outputs=[gr.Textbox(label="Summarized text",lines=4)], |
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title="@GenAILearniverse Project 1: Text Summarizer", |
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description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT") |
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demo.launch() |