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app.py

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+from transformers import pipeline
+
+# Load the model
+pipe = pipeline("text-classification", model="mgbam/roberta-yelp-genomic-bottleneck")
+
+# Gradio app
+import gradio as gr
+
+def classify_text(text):
+    results = pipe(text)
+    return results
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=classify_text,
+    inputs="text",
+    outputs="json",
+    title="Text Classification",
+    description="Classify text using the RoBERTa-Yelp-Genomic-Bottleneck model."
+)
+
+if __name__ == "__main__":
+    interface.launch()
+

requirements.txt

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+transformers
+torch
+gradio
+
+