Add application file

app.py

@@ -137,8 +137,8 @@ demo = gr.Interface(fn=classify_output, inputs=txtbx, outputs=txtbxopt,
                     description = """
                     
                     ¡Hello! This app showcases two machine learning models to classify items and phrases into the EEMM grid. 
-                    It will output a classification for dimensions as *Cognition, Self, Affect, Motivation, Attention, Overt Behavior or Context*. I
-                    t Will also output levels as *Social, Psychological or Physical*. 
+                    It will output a classification for dimensions as *Cognition, Self, Affect, Motivation, Attention, Overt Behavior or Context*.
+                    It will also output levels as *Social, Psychological or Physical*. 
                     You will also see the probability assigned by the model in parentheses (e.g: Affect (0.92)) 
 
                     This is a proof of concept, so the model will not be perfect right away and may make some mistakes.