Update app.py

app.py

@@ -6,7 +6,7 @@ vs_examples = [
 	["In child protective services, further providing for definitions, for immunity from liability"], 
 	["Lol what? Measles is a real thing. Get vaccinated"]]
 vs_title = "Vaccine Sentiment Task"
-vs_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 have true labels 0,1,2 respectively. For more details, please refer to the VS2 dataset description in our paper (linked provided in the corresponding Hugging Face repository)."
+vs_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 have true labels 0,1,2 respectively. For more details, please refer to the VS2 dataset description in our paper (link provided in the corresponding Hugging Face repository)."
 
 vs_predictor_bert = ktrain.load_predictor('vs/bert')
 vs_predictor_mental = ktrain.load_predictor('vs/mentalbert')
@@ -38,7 +38,7 @@ hm_examples = [
 	["It's odd how humans are considered predators when they have a heart attack and run like mad when a small insect is running straight towards them."], 
 	["The older we get the less likely we are to view a sudden massive heart attack as a tragedy than a stroke of good luck."]]
 hm_title = "Health Mention Task"
-hm_desc = "Enter health-related tweets to generate classification from 3 models (BERT, MentalBERT, PHS-BERT). Label 0='Figurative Mentions', 1='Non-Health Mentions', 2='Health mentions'. The three provided examples have true labels 0,1,2 respectively. For more details, please refer to the RHMD dataset description in our paper (linked provided in the corresponding Hugging Face repository)."
+hm_desc = "Enter health-related tweets to generate classification from 3 models (BERT, MentalBERT, PHS-BERT). Label 0='Figurative Mentions', 1='Non-Health Mentions', 2='Health mentions'. The three provided examples have true labels 0,1,2 respectively. For more details, please refer to the RHMD dataset description in our paper (link provided in the corresponding Hugging Face repository)."
 
 hm_predictor_bert = ktrain.load_predictor('hm/bert')
 hm_predictor_mental = ktrain.load_predictor('hm/mentalbert')