Add 'template' and 'bert-mouth' visuals back

app.py

@@ -470,7 +470,7 @@ def run():
     we may take the sentence we wish to classify and append the text "Overall, this
     movie was ____." and feed it into a language model like so:
     ''')
-    # st.image('assets/bert-mouth.png', use_column_width=True)
+    st.image('assets/bert-mouth.png', use_column_width=True)
     st.markdown('''
     By measuring whether the language model assigns a higher probability to
     words that are associated with a **positive** sentiment ("good", "great",
@@ -496,7 +496,7 @@ def run():
     a number of *trigger tokens* that will automatically be learned by the
     model and the *predict token* that the model will fill in:
     ''')
-    # st.image('assets/template.png', use_column_width=True)
+    st.image('assets/template.png', use_column_width=True)
     st.markdown(
     '''
     In each iteration of the search process: