Update app.py

app.py

@@ -68,8 +68,12 @@ if __name__ == '__main__':
 # 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.
-**Forked from [mbahrami/Auto-Complete_Semantic](https://huggingface.co/spaces/mbahrami/Auto-Complete_Semantic).**
-**Disclaimer:** The behind idea is to compare our models that included Guarani during pre-training vs. the models that do not have saw it. That is, the multilingual ones: XLM-RoBERTa, mBERT and Spanish BERTs (BETO and PLAN-TL-RoBERTa). Additionally, we include English models: BERT and RoBERTa, for comparison reasons.
+
+## Source
+Forked from **[mbahrami/Auto-Complete_Semantic](https://huggingface.co/spaces/mbahrami/Auto-Complete_Semantic)** with *[osanseviero/fork_a_repo](https://huggingface.co/spaces/osanseviero/fork_a_repo)*.
+
+## Disclaimer
+The behind idea is to compare our models that included Guarani during pre-training vs. the models that do not have saw it. That is, the multilingual ones: XLM-RoBERTa, mBERT and Spanish BERTs (BETO and PLAN-TL-RoBERTa). Additionally, we include English models: BERT and RoBERTa, for comparison reasons.
 """)
         history_keyword_text = st.text_input("Enter users's history <Keywords Match> (optional, i.e., 'Premio Cervantes')", value="")