Update app.py

app.py

@@ -140,8 +140,8 @@ def main():
         <small style="font-size:20px; color: #2f2f2f"><br/>Why compare pretrained models <b>before fine-tuning</b>?</small><br/><small style="font-size:18px; color: #7f7f7f">Pretrained BERT models can be used as is, <a href="https://ajitrajasekharan.github.io/2021/01/02/my-first-post.html"><b>with no fine tuning to perform tasks like NER.</b><br/></a>This can be done ideally by using both fill-mask and CLS predictions, or minimally using fill-mask predictions alone if they are adequate</small>
         """, unsafe_allow_html=True)
 
-  st.write("This app can be used to examine both model prediction for a masked  position as well as the neighborhood of CLS vector")
-  st.write("   - To examine model prediction for a position, enter the token [MASK] or <mask>")
+  st.write("This app can be used to examine both fill-mask predictions as well as the neighborhood of CLS vector")
+  st.write("   - To examine fill-mask predictions, enter the token [MASK] or <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")
   st.sidebar.slider("Select count of predictions to display", 1 , 50, 20,key='my_slider',on_change=on_results_count_change) #some times it is possible to have less words