updated text underneath headers of tabs

app.py

@@ -98,7 +98,7 @@ if active_tab == "Nearest neighbours":
     
     with st.container():
         st.markdown("## Nearest Neighbours")
-        st.markdown('###### Here you can extract the nearest neighbours to a chosen lemma. Please select one or more time slices and the preferred number of nearest neighbours.')
+        st.markdown('Here you can extract the nearest neighbours to a chosen lemma. Please select one or more time slices and the preferred number of nearest neighbours.')
         target_word = st.multiselect("Enter a word", options=all_models_words, max_selections=1)
         if len(target_word) > 0:
             target_word = target_word[0]
@@ -160,7 +160,7 @@ elif active_tab == "Cosine similarity":
         eligible_models_1 = []
         eligible_models_2 = []
         st.markdown("## Cosine similarity")
-        st.markdown('###### Here you can extract the cosine similarity between two lemmas. Please select a time slice for each lemma. You can also calculate the cosine similarity between two vectors of the same lemma in different time slices.')
+        st.markdown('Here you can extract the cosine similarity between two lemmas. Please select a time slice for each lemma. You can also calculate the cosine similarity between two vectors of the same lemma in different time slices.')
         col1, col2 = st.columns(2)
         col3, col4 = st.columns(2)
         with col1:
@@ -194,7 +194,7 @@ elif active_tab == "Cosine similarity":
 # 3D graph tab
 elif active_tab == "3D graph":
     st.markdown("## 3D graph")
-    st.markdown('###### Here you can generate a 3D representation of the semantic space surrounding a target lemma. Please choose the lemma and the time slice.')
+    st.markdown('Here you can generate a 3D representation of the semantic space surrounding a target lemma. Please choose the lemma and the time slice.')
     
     col1, col2 = st.columns(2)
     
@@ -237,7 +237,7 @@ elif active_tab == "Dictionary":
     
     with st.container():
         st.markdown('## Dictionary')
-        st.markdown('###### Search a word in the Liddell-Scott-Jones dictionary (only Greek, no whitespaces).')
+        st.markdown('Search a word in the Liddell-Scott-Jones dictionary (only Greek, no whitespaces).')
 
 
         all_lemmas = load_all_lemmas()