Rem subreddit that took up all the tokens. Add ceo example.

app.py

@@ -83,7 +83,9 @@ SUBREDDITS = [
     "GetMotivated",
     "pokemongo",
     "news",
-    "fffffffuuuuuuuuuuuu",
+    # removing below subreddit as most of the tokens are taken up it:
+    # ['ff', '##ff', '##ff', '##fu', '##u', '##u', '##u', '##u', '##u', '##u', '##u', '##u', '##u', '##u', '##u', ...]
+    #"fffffffuuuuuuuuuuuu",
     "Fitness",
     "Showerthoughts",
     "OldSchoolCool",
@@ -516,12 +518,12 @@ Note: if app seems frozen, refreshing webpage may help. Sorry for the inconvenie
 
 article = "The source code to generate the fine-tuned models can be found/reproduced here: https://github.com/2dot71mily/causing_gendering_pronouns_two"
 
-scientist_example = [
+ceo_example = [
     REDDIT,
     [BERT_LIKE_MODELS[0]],
     "True",
     "True",
-    'She was a very well regarded scientist and her work won many awards.',
+    "She is the founder and CEO. She has led company growth from fledging start up to unicorn.",
 ]
 building_example = [
     WIKIBIO,
@@ -535,7 +537,7 @@ death_date_example = [
     BERT_LIKE_MODELS,
     "False",
     "True",
-    'Died in DATE, she was recognized for her great accomplishments to the field of teaching.'
+    'Died in DATE, she was recognized for her great accomplishments to the field of computer science.'
 ]
 neg_reddit_example = [
     REDDIT,
@@ -556,7 +558,7 @@ gr.Interface(
         gr.CheckboxGroup(
             BERT_LIKE_MODELS,
             type="value",
-            label="Pick optional BERT base uncased model.",
+            label="Optional BERT base uncased model(s).",
         ),
         gr.Dropdown(
             ["False", "True"],
@@ -592,5 +594,5 @@ gr.Interface(
     title=title,
     description=description,
     article=article,
-    examples=[scientist_example, building_example, death_date_example, neg_reddit_example]
+    examples=[ceo_example, building_example, death_date_example, neg_reddit_example]
 ).launch(debug=True)