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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="mgbam/roberta-yelp-genomic-bottleneck") |
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def classify_text(text): |
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results = pipe(text) |
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formatted_results = [ |
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f"Label: {result['label']}, Score: {result['score']:.2f}" for result in results |
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] |
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return "\n".join(formatted_results) |
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interface = gr.Interface( |
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fn=classify_text, |
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inputs="text", |
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outputs="text", |
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title="Text Classification", |
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description="Classify text using the RoBERTa-Yelp-Genomic-Bottleneck model." |
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) |
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if __name__ == "__main__": |
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interface.launch() |
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