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app.py

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+import gradio as gr
+from transformers import pipeline
+
+def fill_mask(text):
+    model_name = "AventIQ-AI/RoBERTa"
+    mask_filler = pipeline("fill-mask", model=model_name)
+    
+    results = mask_filler(text)
+    
+    output = "\n".join([f"{i+1}. {res['sequence']} (Confidence: {res['score']:.4f})" for i, res in enumerate(results)])
+    return output
+
+iface = gr.Interface(
+    fn=fill_mask,
+    inputs=gr.Textbox(label="Input Text (Use <mask> for missing word)"),
+    outputs=gr.Textbox(label="Predictions"),
+    title="RoBERTa Fill Mask",
+    description="Enter a sentence with <mask>, and the RoBERTa model will predict the missing word."
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+torch
+transformers
+gradio
+sentencepiece