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from transformers import pipeline |
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import gradio as gr |
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pipe = pipeline("text-classification", model="AbrorBalxiyev/my_awesome_model", return_all_scores=True) |
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def classify_text(text): |
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results = pipe(text)[0] |
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results.sort(key=lambda x: x["score"], reverse=True) |
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result = "" |
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for item in results: |
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percentage = item["score"] * 100 |
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result += f"{item['label']}: {percentage:.1f}%\n" |
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return result |
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iface = gr.Interface( |
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fn=classify_text, |
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inputs=gr.Textbox(placeholder="Enter text to classify...", label="Input Text"), |
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outputs=gr.Textbox(label="Classification Results"), |
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title="Text Category Classification", |
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description="Enter text to see its category classification percentages.", |
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examples=[ |
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["Mercedes is one of the best quality cars."], |
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["Perevalda Damas va Lacetti avtomobillari avtoxalokatga uchradi"], |
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["Kitob o'qish foydali"] |
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] |
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) |
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iface.launch(share=True) |