Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+ner = pipeline('ner')
+
+def merged_words(tokens):
+    m = []
+    for token in tokens:
+        if m and token['entity'].startswith('I-') and m[-1]['entity'].endswith(token['entity'][2:]):
+            last_token = m[-1]
+            last_token['word'] += token['word'].replace('##', '')
+            last_token['end'] = token['end']
+            last_token['score'] = (last_token['score'] + token[score]) / 2
+        else:
+            m.append(token)
+    return m
+
+def named(input):
+    output = ner(input)
+    merged_words = merged_words(output)
+    return {'text': input, 'entities': merged_words}
+
+a = gr.Interface(fn=name, 
+                 inputs=[gr.Textbox(label="Text input", lines= 2)],
+                 outputs=[gr.HighlightedText(label='Text with entities')],
+                 title='Named Entity Recognition', examples=["My name is Andrew, I'm building DeeplearningAI and I live in California", "My name is Poli, I live in Vienna and work at HuggingFace"])
+a.launch()
+