Update app.py

app.py

@@ -35,9 +35,6 @@ def tokenize_and_convert_to_ids(text):
 
 def ner_tagging(text_1):
 
-	with open("vocab.json",'r') as f:
-		vocab = json.load(f)
-
 	with open('mapping.json','r') as f:
 		mapping = json.load(f)
 
@@ -45,7 +42,6 @@ def ner_tagging(text_1):
                                   custom_objects={'CustomNonPaddingTokenLoss':CustomNonPaddingTokenLoss},
                                   compile=False)  
 
-	lookup_layer = keras.layers.StringLookup(vocabulary=vocab['tokens'])
 
 	sample_input = tokenize_and_convert_to_ids(text_1)
 	sample_input = tf.reshape(sample_input, shape=[1, -1])
@@ -57,9 +53,13 @@ def ner_tagging(text_1):
 	return prediction
 
 text_1 = gr.inputs.Textbox(lines=5)
-
 ner_tag = gr.outputs.Textbox()
 
+with open("vocab.json",'r') as f:
+	vocab = json.load(f)
+
+lookup_layer = keras.layers.StringLookup(vocabulary=vocab['tokens'])
+
 iface = gr.Interface(ner_tagging, 
 	inputs=text_1,outputs=ner_tag, examples=[['EU rejects German call to boycott British lamb .'], 
 	["Wednesday's U.S. Open draw ceremony revealed that both title holders should run into their first serious opposition in the third round."]], title="Named Entity Recognition with Transformers",