import streamlit as st

title = "Key Takeaways"
description = "The key takeaways from this exploration"
date = "2022-01-26"
thumbnail = "images/huggingface_logo.png"

def run_article():
  st.markdown("""
  # Conclusion

  Here are some of the main ideas we have conveyed in this exploration: 
  - Defining hate speech is hard and changes depending on your context and goals.
  - Capturing a snapshot of what you've defined to be hate speech in a dataset is hard.
  - Models learn lots of different things based on the data it sees, and that can include things you didn't intend for them to learn.

  Action items?
  """)