Updated Description

app.py

@@ -37,8 +37,9 @@ def get_ner(sentence):
 
 iface = gr.Interface(get_ner,
                      gr.Textbox(placeholder="Enter sentence here..."),
-                     ["highlight"], examples=['लगातार हमलावर हो रहे शिवपाल और राजभर को सपा की दो टूक, चिट्ठी जारी कर कहा- जहां जाना चाहें जा सकते हैं', 'ಶರಣ್ ರ ನೀವು ನೋಡಲೇಬೇಕಾದ ಟಾಪ್ 5 ಕಾಮಿಡಿ ಚಲನಚಿತ್ರಗಳು'], title='IndicNER',
-                     article='IndicNER is a model trained to complete the task of identifying named entities from sentences in Indian languages. Our model is specifically fine-tuned to the 11 Indian languages mentioned above over millions of sentences. The model is then benchmarked over a human annotated testset and multiple other publicly available Indian NER datasets. The 11 languages covered by IndicNER are: Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, Telugu.'
+                     ["highlight"], description='The 11 languages covered by IndicNER are: Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, Telugu.',
+                     examples=['लगातार हमलावर हो रहे शिवपाल और राजभर को सपा की दो टूक, चिट्ठी जारी कर कहा- जहां जाना चाहें जा सकते हैं', 'ಶರಣ್ ರ ನೀವು ನೋಡಲೇಬೇಕಾದ ಟಾಪ್ 5 ಕಾಮಿಡಿ ಚಲನಚಿತ್ರಗಳು'], title='IndicNER',
+                     article='IndicNER is a model trained to complete the task of identifying named entities from sentences in Indian languages. Our model is specifically fine-tuned to the 11 Indian languages mentioned above over millions of sentences. The model is then benchmarked over a human annotated testset and multiple other publicly available Indian NER datasets.'
                      )
 
 iface.launch(enable_queue=True)