Added Highlight to the output

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForTokenClassification
 from transformers import pipeline
+import re
 
 description = "Named Entity Recognition Using BERT"
 title = "NERBERT"
@@ -10,7 +11,13 @@ def findNER(example):
   tokenizer = AutoTokenizer.from_pretrained("dslim/bert-base-NER")
   model = AutoModelForTokenClassification.from_pretrained("dslim/bert-base-NER")
   ner_pipeline = pipeline("ner", model=model, tokenizer=tokenizer)
-  return ner_pipeline(example)
+  pipeline_output = ner_pipeline(example)
+  final_output = []
+  # all_words = re.split(r'[^a-zA-Z0-9\s]', example)
+  for _ in pipeline_output:
+    final_output.extend([(_['word'], _['entity'])])
+  
+  return final_output
 
-interface = gr.Interface(fn=findNER, inputs='text', outputs='text', examples=examples, description=description, title=title)
+interface = gr.Interface(fn=findNER, inputs='text', outputs=['highlight'], examples=examples, description=description, title=title, interpretation='default')
 interface.launch()