Update app.py

app.py

@@ -7,27 +7,27 @@ examples = [
 	["In child protective services, further providing for definitions, for immunity from liability"], 
 	["Lol what? Measles is a real thing. Get vaccinated"]]
 title = "Vaccine Sentiment Task - VS2"
-desc = "Enter vaccine-related tweets to generate sentiment from 3 models (BERT, MentalBERT, PHS-BERT). Label 0='vaccine critical', 1='neutral', 2='vaccine supportive'. The three provided examples are labelled 0,1,2 respectively. For details about VS2, refer to our paper (linked provided in https://huggingface.co/publichealthsurveillance/PHS-BERT)."
+desc = "Enter vaccine-related tweets to generate sentiment from 3 models (BERT, MentalBERT, PHS-BERT). Label 0='vaccine critical', 1='neutral', 2='vaccine supportive'. The three provided examples are labelled 0,1,2 respectively. For details about VS2, please refer to our paper (linked provided in the corresponding Hugging Face repository)."
 
 predictor_bert = ktrain.load_predictor('bert')
 predictor_mental = ktrain.load_predictor('mentalbert')
 predictor_phs = ktrain.load_predictor('phsbert')
 
-def bert(text):
+def BERT(text):
 	results = predictor_bert.predict(str(text))
 	return str(results)
 	
-def mentalbert(text):
+def MentalBERT(text):
 	results = predictor_mental.predict(str(text))
 	return str(results)
 	
-def phsbert(text):
+def PHS-BERT(text):
 	results = predictor_phs.predict(str(text))
 	return str(results)
 
-bert_io = gr.Interface(fn=bert, inputs="text", outputs="text")
-mental_io = gr.Interface(fn=mentalbert, inputs="text", outputs="text")
-phs_io = gr.Interface(fn=phsbert, inputs="text", outputs="text")
+bert_io = gr.Interface(fn=BERT, inputs="text", outputs="text")
+mental_io = gr.Interface(fn=MentalBERT, inputs="text", outputs="text")
+phs_io = gr.Interface(fn=PHS-BERT, inputs="text", outputs="text")
 
 Parallel(bert_io, mental_io, phs_io, 
 	examples=examples,