Update app.py

app.py

@@ -50,8 +50,6 @@ description_GNER = """
 A T5 model tuned to perform text generation, and predict which characters are present in the report. Note that, in the Hall and Van de Castle, the character lists never includes the dreamer. Hence, if you (willingly or not) enter a report that does not contain another character reference, the model will/should (correctly) produce an empty string. Moreover, it is likely that the produced list of CHAR could be longer than the one produced by the SA model, as not all CHAR might be associated with emotions. 
 """
 
-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."],
@@ -75,7 +73,7 @@ interface_words = gr.Interface(
             outputs="text",
             title=title,
             description=description_main,
-            examples=example_main,
+            examples=[["en", "it", "pl"]],
 )
 
 # interface_model_L = gr.Interface(