Create app.py

app.py

@@ -0,0 +1,19 @@
+import gradio as gr
+from transformers import pipeline
+
+get_completion = pipeline("ner", model="dslim/bert-base-NER")
+
+def ner(input):
+    output = get_completion(input)
+    return {"text": input, "entities": output}
+
+gr.close_all()
+demo = gr.Interface(fn=ner,
+                    inputs=[gr.Textbox(label="Text to find entities", lines=2)],
+                    outputs=[gr.HighlightedText(label="Text with entities")],
+                    title="Named Entity Recognition - NER ",
+                    description="Find entities using the `dslim/bert-base-NER` model under the hood!",
+                    allow_flagging="never",
+                    #Here we introduce a new tag, examples, easy to use examples for your application
+                    examples=["My name is Andrew and I live in California", "My name is Poli and work at HuggingFace"])
+demo.launch()