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app.py
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# Necessary imports
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import gradio as gr
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from classytext.classifier.predict import ZeroShotTextClassification
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# Examples to display in the interface
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examples = [
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[
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"I have a problem with my iPhone that needs to be resolved asap!",
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"urgent, not urgent, phone, tablet, computer",
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False,
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],
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[
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"Angela Merkel is a politician in Germany and leader of the CDU",
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"politics, economy, entertainment, environment",
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False,
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],
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[
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"Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!",
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"refund, legal, faq",
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True,
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],
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]
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# Title and description and article for the interface
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title = "Zero Shot Text Classification"
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description = "Classify text using zero-shot classification with ModernBERT-large zeroshot model! Provide a text input and a list of candidate labels separated by commas. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2412.13663' target='_blank'>Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference</a> | <a href='https://huggingface.co/MoritzLaurer/ModernBERT-large-zeroshot-v2.0' target='_blank'>Model Page</a></p>"
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# Launch the interface
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demo = gr.Interface(
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fn=ZeroShotTextClassification,
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inputs=[
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gr.Textbox(label="Input", placeholder="Enter text to classify"),
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gr.Textbox(
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label="Candidate Labels",
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placeholder="Enter candidate labels separated by commas",
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),
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gr.Checkbox(label="Multi-Label", value=False),
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],
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outputs=gr.Label(label="Classification"),
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title=title,
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description=description,
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article=article,
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examples=examples,
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cache_examples=True,
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cache_mode="lazy",
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theme="Soft",
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flagging_mode="never",
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)
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demo.launch(debug=False)
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