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app.py

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+from transformers import pipeline
+import gradio as gr
+
+ner_model = pipeline(
+    "ner",
+    model="dslim/bert-base-NER",
+    aggregation_strategy="simple"
+)
+
+def ner_inference(text):
+    return ner_model(text)
+
+interface = gr.Interface(
+    fn=ner_inference,
+    inputs=gr.Textbox(lines=5, placeholder="Enter text"),
+    outputs=gr.JSON(),
+    title="NER using Hugging Face",
+    description="Deployed with Gradio on HF Spaces"
+)
+
+if __name__ == "__main__":
+    interface.launch()

requirements.txt

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+transformers
+torch
+gradio