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app.py
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import gradio as gr
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import re
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from transformers import pipeline
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sp_model = "SineTheta/Spam_and_bully_detection"
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ca_model = "SineTheta/Spam_and_bully_detection"
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sp_analysis = pipeline("text-classification", model=sp_model, tokenizer=sp_model)
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ca_analysis = pipeline("text-classification", model=ca_model, tokenizer=ca_model)
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def bullying_analysis(language, text):
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if language == 'English':
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results = sp_analysis(text)
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elif language == 'French':
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results = ca_analysis(text)
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return results[0]["label"], round(results[0]["score"], 5)
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gradio_ui = gr.Interface(
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fn=bullying_analysis,
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title="CyberBullying Detector (Spanish/Catalan)",
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description="Enter some text and check if the model detects bullying.",
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inputs=[
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gr.inputs.Radio(['Spanish','Catalan'],label='Language',),
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gr.inputs.Textbox(lines=5, label="Paste some text here"),
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],
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outputs=[
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gr.outputs.Textbox(label="Label"),
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gr.outputs.Textbox(label="Score"),
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],
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examples=[
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['Spanish', "Eres mas alto que un pino y mas tonto que un pepino!"],
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['Catalan', "Ets un barrufet!"],
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['Spanish', "Estas mas gordo que una foca!"],
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['Catalan', "Ets mes lleig que un pecat!"],
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],
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)
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gradio_ui.launch()
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