Update app.py

app.py

@@ -4,6 +4,9 @@ import torch
 import string
 
 
+bert_tokenizer = None
+bert_model = None
+
 from transformers import BertTokenizer, BertForMaskedLM
 
 st.set_page_config(page_title='Qualitative pretrained model eveluation', page_icon=None, layout='centered', initial_sidebar_state='auto')
@@ -68,6 +71,8 @@ def get_bert_prediction(input_text,top_k):
  
 def run_test(sent,top_k):
   start = None
+  if (bert_tokenizer is None):
+        bert_tokenizer, bert_model  = load_bert_model(model_name)
   with st.spinner("Computing"):
           start = time.time()
           try:
@@ -92,8 +97,7 @@ st.write("   - To examine model prediction for a position, enter the token [MASK
 st.write("   - To examine just the [CLS] vector, enter a word/phrase or sentence. Example: eGFR or EGFR or non small cell lung cancer")
 top_k = st.sidebar.slider("Select how many predictions do you need", 1 , 50, 20) #some times it is possible to have less words
 print(top_k)
-bert_tokenizer = None
-bert_model = None
+