Create app.py

app.py

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+# 🔍 Masked Word Predictor | CPU-only HF Space
+
+import gradio as gr
+from transformers import pipeline
+
+# Load the fill-mask pipeline once at startup
+fill_mask = pipeline("fill-mask", model="distilroberta-base", device=-1)
+
+def predict_mask(sentence: str, top_k: int):
+    if "[MASK]" not in sentence:
+        return [{"sequence": "Error: include [MASK] in your sentence.", "score": 0.0}]
+    preds = fill_mask(sentence, top_k=top_k)
+    return [
+        {"sequence": p["sequence"], "score": round(p["score"], 3)}
+        for p in preds
+    ]
+
+with gr.Blocks(title="🔍 Masked Word Predictor") as demo:
+    gr.Markdown(
+        "# 🔍 Masked Word Predictor\n"
+        "Enter a sentence with one `[MASK]` token and see the model’s top predictions."
+    )
+
+    with gr.Row():
+        sentence = gr.Textbox(
+            lines=2,
+            placeholder="The capital of France is [MASK].",
+            label="Input Sentence"
+        )
+        top_k = gr.Slider(
+            minimum=1, maximum=10, step=1, value=5,
+            label="Top K Predictions"
+        )
+    predict_btn = gr.Button("Predict", variant="primary")
+
+    results = gr.Dataframe(
+        headers=["sequence", "score"],
+        datatype=["str", "number"],
+        wrap=True,
+        interactive=False,
+        label="Predictions"
+    )
+
+    predict_btn.click(
+        predict_mask,
+        inputs=[sentence, top_k],
+        outputs=results
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0")