Update app.py

app.py

@@ -6,7 +6,7 @@ import string
 bert_tokenizer = None
 bert_model = None
 top_k = 20
-model_name = None
+model_name = 'ajitrajasekharan/biomedical'
 
 from transformers import BertTokenizer, BertForMaskedLM
 
@@ -123,10 +123,9 @@ def on_model_change2():
   bert_tokenizer, bert_model  = load_bert_model(model_name)
   
 def init_selectbox():
-  option = st.selectbox(
+  st.selectbox(
      'Choose any of these sentences or type any text below',
      ('', "[MASK] who lives in New York and works for XCorp suffers from Parkinson's", "Lou Gehrig who lives in [MASK] and works for XCorp suffers from Parkinson's","Lou Gehrig who lives in New York and works       for [MASK] suffers from Parkinson's","Lou Gehrig who lives in New York and works for XCorp suffers from [MASK]","[MASK] who lives in New York and works for XCorp suffers from Lou Gehrig's", "Parkinson who      lives in [MASK] and works for XCorp suffers from Lou Gehrig's","Parkinson who lives in New York and works for [MASK] suffers from Lou Gehrig's","Parkinson who lives in New York and works for XCorp suffers      from [MASK]","Lou Gehrig","Parkinson","Lou Gehrigh's is a [MASK]","Parkinson is a [MASK]","New York is a [MASK]","New York","XCorp","XCorp is a [MASK]","acute lymphoblastic leukemia","acute lymphoblastic       leukemia is a [MASK]"),on_change=on_option_change,key='my_choice') 
-  return option
   
 
 
@@ -154,14 +153,14 @@ def main():
   #  with st.spinner("Computing"):
   try:
       
-      model_name = st.sidebar.selectbox(label='Select Model to Apply',  options=['ajitrajasekharan/biomedical', 'bert-base-cased','bert-large-cased','microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext','allenai/scibert_scivocab_cased','dmis-lab/biobert-v1.1'], index=0,  key = "my_model1",on_change=on_model_change1)
-      option = init_selectbox()
-      input_text = st.text_input("Enter text below", "",on_change=on_text_change,key='my_text')
-      custom_model_name = st.text_input("Model not listed on left? Type the model name (fill-mask BERT models only)", "",key="my_model2",on_change=on_model_change2)
-      if (len(custom_model_name) > 0):
-        model_name = custom_model_name
-        st.info("Custom model selected: " + model_name)
-        bert_tokenizer, bert_model  = load_bert_model(model_name)
+      st.sidebar.selectbox(label='Select Model to Apply',  options=['ajitrajasekharan/biomedical', 'bert-base-cased','bert-large-cased','microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext','allenai/scibert_scivocab_cased','dmis-lab/biobert-v1.1'], index=0,  key = "my_model1",on_change=on_model_change1)
+      init_selectbox()
+      st.text_input("Enter text below", "",on_change=on_text_change,key='my_text')
+      st.text_input("Model not listed on left? Type the model name (fill-mask BERT models only)", "",key="my_model2",on_change=on_model_change2)
+      #if (len(custom_model_name) > 0):
+       # model_name = custom_model_name
+      #  st.info("Custom model selected: " + model_name)
+      #  bert_tokenizer, bert_model  = load_bert_model(model_name)
       #if len(input_text) > 0:
       #  run_test(input_text,top_k,model_name)
       #else: