Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+ner_pipeline = pipeline(task='ner', model='cwchang/ner_model', device=-1)
+
+def ner(text):
+    output = ner_pipeline(text, aggregation_strategy="simple")
+    return {"text": text, "entities": output}
+
+demo = gr.Interface(
+    fn=ner,
+    inputs=gr.Textbox(placeholder="Please enter a sentence here..."),
+    outputs=gr.HighlightedText(),
+    examples=[["Emily Johnson will attend a United Nations meeting in New York on December 5, 2023."],
+        ["Microsoft plans to launch its new tech product in Tokyo at the beginning of 2024."],
+        ["Professor Michael Brown from the University of Toronto will present his latest research on climate change."],
+        ["The famous Christ the Redeemer statue in Rio de Janeiro, Brazil, is scheduled for renovation in July 2023."],
+        ["Maria Fernandez will open a new art gallery in Paris in June 2023."],
+        ["The 2023 World Economic Forum is set to take place in Davos, Switzerland, expected to attract numerous international leaders."],
+        ["Japanese scientist Ichiro Tanaka discovered a new renewable energy technology at the University of Tokyo."],
+        ["The International Red Cross will initiate a humanitarian aid project in Nairobi, Kenya, in May 2023."],
+        ["The Sydney Opera House in Australia will host a special concert during Christmas 2023."],
+        ["The history museum in Berlin, Germany, will organize a World War II exhibition in January 2024."],]
+    )
+
+demo.launch(debug=True)