Update app.py

app.py

@@ -39,7 +39,6 @@ The current model achieves an accuracy of 90% on out-of-distribution evaluation.
 Use the next page to check if your test-items (i.e. adjective, noun and hypernyms) were part of the training data!"""
 
 examples = [["A red car is a vehicle"], ["A fake smile is a smile"], ["A small cat is a small animal"]]
-examples_w = [["red,car,vehicle"], ["fake,smile"], ["small,cat,animal"]]
 
 
 interface_words = gr.Interface(
@@ -49,6 +48,14 @@ interface_words = gr.Interface(
             examples=examples_w,
 )
 
+
+
+description_e = """
+You can use this page to test if a set of words was included in the training data used to tune the model. As in the samples below, use as input a series of words separated solely by a comma (e.g. *red,car,vehicle*).
+"""
+
+examples_w = [["red,car,vehicle"], ["fake,smile"], ["small,cat,animal"]]
+
 interface_model = gr.Interface.load(
             "huggingface/lorenzoscottb/bert-base-cased-PLANE-ood-2",
             description=description,