Update app.py

app.py

@@ -15,13 +15,13 @@ def check_lang(lang_acronym):
     else: 
         return "False"
     
-title = "DSA II"
+title = "DSA: version II"
 
 description_main = """
-A set of models to perform sentiment analysis. Choose between Large-Multilingual or Small-En-only. 
+A set of pre-trained LLMs tuned to perform sentiment analysis. You can choose between a Large-Multilingual or Base-English-only model. 
 
-Use the interface to check if a language is included in the multilingual model, using language acronyms (e.g. it for Italian).
-Select one of the two pages to start querying one of the two models.
+Use the current interface to check if a language is included in the multilingual model, using language acronyms (e.g. it for Italian).
+Click on one of the upper buttons to select and start querying one of the two models.
 """
 
 description_L = """
@@ -32,6 +32,8 @@ description_S = """
 A BERT-base-cased model pre-trained and tuned on English data.
 """
 
+example_main = ["en", "it", "pl"]
+
 examples = [
     ["I was followed by the blue monster but was not scared. I was calm and relaxed."],
     ["Ero seguito dal mostro blu, ma non ero spaventato. Ero calmo e rilassato."],
@@ -42,7 +44,9 @@ interface_words = gr.Interface(
             fn=check_lang,
             inputs="text", 
             outputs="text",
+            title=title,
             description=description_main,
+            examples=example_main,
 )
 
 interface_model_L = gr.Interface.load(