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Download pages/01_BERT_Topic_Modeling.py from shrut27/CRC-Webapp: direct link, hf CLI and curl.
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https://huggingface.co/spaces/shrut27/CRC-Webapp/resolve/refs%2Fpr%2F13/pages/01_BERT_Topic_Modeling.py
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hf download hf://spaces/shrut27/CRC-Webapp@refs/pr/13/pages/01_BERT_Topic_Modeling.py
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curl -L -o 01_BERT_Topic_Modeling.py https://huggingface.co/spaces/shrut27/CRC-Webapp/resolve/refs%2Fpr%2F13/pages/01_BERT_Topic_Modeling.py
1.07 kB
| import streamlit as st | |
| def bert_intro(): | |
| st.title("Topic Modeling with BERT") | |
| st.markdown("BERT (BERTopic): Explanation of the advanced NLP technique used for analyzing the data, and its application in this project.") | |
| st.header("Process Flow: Step-by-step breakdown of the analysis process, from data gathering to insights extraction.") | |
| def youth_classification(): | |
| st.title("Youth Classification") | |
| def sentiment_analysis(): | |
| st.title("Sentiment Analysis") | |
| def bert_topic_modeling(): | |
| st.title("Topic Modeling") | |
| sidebar_pages = ["Introduction", "Youth Classification", "Sentiment Analysis", "Topic Modeling"] | |
| def main(): | |
| st.sidebar.title("Navigation") | |
| page = st.sidebar.selectbox("Select page:", sidebar_pages) | |
| if page == "Introduction": | |
| bert_intro() | |
| elif page == "Youth Classification": | |
| youth_classification() | |
| elif page == "Sentiment Analysis": | |
| sentiment_analysis() | |
| elif page == "Topic Modeling": | |
| bert_topic_modeling() | |
| if __name__ == "__main__": | |
| main() |