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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?
""")
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