copy pasted from ChatGPT

app.py

@@ -0,0 +1,24 @@
+from transformers import pipeline
+import gradio as gr
+
+# Load the NER pipeline
+ner_model = pipeline("ner", model="dslim/bert-base-NER", aggregation_strategy="simple")
+
+def extract_named_entities(text):
+    # Use the NER model to extract named entities
+    entities = ner_model(text)
+    # Format the output for better readability
+    return [{"Entity": ent["entity_group"], "Text": ent["word"], "Score": round(ent["score"], 3)} for ent in entities]
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=extract_named_entities,
+    inputs=gr.Textbox(lines=5, label="Input Text"),
+    outputs=gr.Dataframe(headers=["Entity", "Text", "Score"], label="Named Entities"),
+    title="Named Entity Recognition",
+    description="Input some text and get the named entities (like names, locations, organizations).",
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()