make text as big as on babel index-page

app.py

@@ -7,22 +7,16 @@ from interfaces.emotion import demo as emotion_demo
 from interfaces.ner import demo as ner_demo
 from interfaces.ner import download_models as download_spacy_models
 
-from spacy import glossary
-
-entities = ["CARDINAL", "DATE", "EVENT", "FAC", "GPE", "LANGUAGE", "LAW", "LOC", "MONEY", "NORP", "ORDINAL", "ORG", "PERCENT", "PERSON", "PRODUCT", "QUANTITY", "TIME", "WORK_OF_ART"]
-ent_dict = glossary.GLOSSARY
-ent_sum = [f'<b>{ent}</b> = <i>{ent_dict[ent]}</i>' for ent in entities ]
 
 with gr.Blocks() as demo:
     gr.Markdown(
         f"""
-        <div style="display: block; text-align: left; padding:0; margin:0;">
-            <h1 style="text-align: center">Babel Machine Demo</h1>
-            <p>This is a demo for text classification using language models finetuned on data labeled by <a href="https://www.comparativeagendas.net/">CAP</a>, <a href="https://manifesto-project.wzb.eu/">Manifesto Project</a>, sentiment, and emotion coding systems.<br>
+        <div style="display: block; text-align: left; padding:0; margin:0;font-family: "Source Sans Pro", Helvetica, sans-serif;">
+            <h1 style="text-align: center;font-size: 17pt;">Babel Machine Demo</h1>
+            <p style="font-size: 14pt;">This is a demo for text classification using language models finetuned on data labeled by <a href="https://www.comparativeagendas.net/">CAP</a>, <a href="https://manifesto-project.wzb.eu/">Manifesto Project</a>, sentiment, and emotion coding systems.<br>
             For the coding of complete datasets, please visit the official <a href="https://babel.poltextlab.com/">Babel Machine</a> site.<br>
             Please note that named entity inputs are case sensitive.<br>
-            For named entity recognition the following labels are used:<br>
-             {' ,&emsp;'.join(ent_sum)}</p>
+            </p>
         </div>
         """)