examples without occupations for gender nudge. break down directions more.

app.py

@@ -297,7 +297,7 @@ place_example = [
     'PLACE',
     "False",
     1,
-    'Born in PLACE, she was a teacher.'
+    'She was raised in PLACE.'
 ]
 
 date_example = [
@@ -317,8 +317,8 @@ subreddit_example = [
     ', '.join(SUBREDDITS),
     'SUBREDDIT',
     "False",
-    3,
-    'I saw in r/SUBREDDIT that she is a hacker.'
+    1,
+    'I saw in r/SUBREDDIT that she was born in 1911.'
 ]
 
 own_model_example = [
@@ -387,8 +387,8 @@ with demo:
         )
 
 
-    gr.Markdown(
-        f"B) Pick a pre-loaded BERT-family model of interest on the right. C) Or select `{OWN_MODEL_NAME}`, then add the mame of any other Hugging Face model that supports the [fill-mask](https://huggingface.co/models?pipeline_tag=fill-mask) task on the right (note: this may take some time to load).")
+    gr.Markdown("B) Pick a pre-loaded BERT-family model of interest on the right.")
+    gr.Markdown(f"Or C) select `{OWN_MODEL_NAME}`, then add the mame of any other Hugging Face model that supports the [fill-mask](https://huggingface.co/models?pipeline_tag=fill-mask) task on the right (note: this may take some time to load).")
 
     with gr.Row():
         model_name = gr.Radio(
@@ -401,7 +401,8 @@ with demo:
         )
 
     gr.Markdown("D) Pick if you want to the predictions normalied to these gendered terms only.")
-    gr.Markdown("E) Also tell the demo what special token you will use in your input text, that you would like replaced with the spectrum of values you listed above, and F) the degree of polynomial fit used for high-lighting possible dose response trend ")
+    gr.Markdown("E) Also tell the demo what special token you will use in your input text, that you would like replaced with the spectrum of values you listed above.") 
+    gr.Markdown("And F) the degree of polynomial fit used for high-lighting possible dose response trend.")
 
 
     with gr.Row():