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Update app.py
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app.py
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@@ -67,7 +67,12 @@ EXAMPLES = [["""
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Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft).
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Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct."""]]
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outputs = [
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gr.Textbox(lines =5,label = "Summarization of text"),
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gr.Number(label="Word Count of given Text"),
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@@ -80,7 +85,7 @@ demo_app = gr.Interface(
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outputs= outputs,
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title = "Text Summarization",
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examples = EXAMPLES,
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#cache_example = True,
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#live = True,
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theme = 'huggingface'
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Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft).
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Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct."""]]
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DESCRIPTION = """We are bombarded with lakhs of characters of text and information and not so much time.
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Text summarization reads the whole documents, based on frequency of words and sentences it understands the
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important sentences and gives us the summary of text.
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We have used a pre-trained model which is a small English pipeline trained on written web text like news, comments for this demo.
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This can be used in organizations that deal with lots of text documents like a law firm where the documents will be summarized in
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one to two paragraph as per our needs."""
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outputs = [
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gr.Textbox(lines =5,label = "Summarization of text"),
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gr.Number(label="Word Count of given Text"),
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outputs= outputs,
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title = "Text Summarization",
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examples = EXAMPLES,
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description = DESCRIPTION,
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#cache_example = True,
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#live = True,
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theme = 'huggingface'
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