Update app.py

app.py

@@ -1,19 +1,17 @@
 import gradio as gr
 from transformers import pipeline
 
-ner = pipeline('ner')
+ner = pipeline('ner', model = "Keyurjotaniya007/xlm-roberta-base-xtreme-multilingual-ner-2.0")
 
 def merge_tokens(tokens):
     merged_tokens = []
     for token in tokens:
         if merged_tokens and token['entity'].startswith('I-') and merged_tokens[-1]['entity'].endswith(token['entity'][2:]):
-            # If current token continues the entity of the last one, merge them
             last_token = merged_tokens[-1]
             last_token['word'] += token['word'].replace('##', '')
             last_token['end'] = token['end']
             last_token['score'] = (last_token['score'] + token['score']) / 2
         else:
-            # Otherwise, add the token to the list
             merged_tokens.append(token)
 
     return merged_tokens
@@ -26,6 +24,5 @@ def named(input):
 a = gr.Interface(fn=named, 
                  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()
-    
+                 title='Multilingual NER', examples=["My name is Keyur Jotaniya, and I live in Rajkot."])
+a.launch()