Update app.py

app.py

@@ -67,13 +67,14 @@ if __name__ == '__main__':
         st.markdown("""
 # Auto-Complete
 This is an example of an auto-complete approach where the next token suggested based on users's history Keyword match & Semantic similarity of users's history (log).
-The next token is predicted per probability and a weight if it is appeared in keyword user's history or there is a similarity to semantic user's history
+The next token is predicted per probability and a weight if it is appeared in keyword user's history or there is a similarity to semantic user's history.
+**Forked from [mbahrami/Auto-Complete_Semantic](https://huggingface.co/spaces/mbahrami/Auto-Complete_Semantic).**
 """)
-        history_keyword_text = st.text_input("Enter users's history <Keywords Match> (optional, i.e., 'Gates')", value="")
+        history_keyword_text = st.text_input("Enter users's history <Keywords Match> (optional, i.e., 'Paraguái')", value="")
         
-        semantic_text = st.text_input("Enter users's history <Semantic> (optional, i.e., 'Microsoft' or 'President')", value="Microsoft")
+        semantic_text = st.text_input("Enter users's history <Semantic> (optional, i.e., 'Premio Cervantes')", value="Premio Cervantes")
         
-        text = st.text_input("Enter a text for auto completion...", value='Where is Bill')
+        text = st.text_input("Enter a text for auto completion...", value='Augusto Roa Bastos ha’e kuimba’e aranduoñemomba’eguasúva')
         model = st.selectbox("Choose a model", ["mmaguero/gn-bert-tiny-cased", "mmaguero/gn-bert-small-cased", "mmaguero/gn-bert-base-cased", "mmaguero/gn-bert-large-cased", "mmaguero/multilingual-bert-gn-base-cased", "mmaguero/beto-gn-base-cased"])
         
         data_load_state = st.text('1.Loading model ...')