Archisman Karmakar
stage1 deberta for seq classification hft model
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2.4 kB
import streamlit as st
import os
import sys
import joblib
import importlib.util
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
from dashboard import show_dashboard
from sentiment_analysis.sentiment_analysis import show_sentiment_analysis
from emotion_analysis import show_emotion_analysis
# from text_transformation import show_text_transformation
def main():
st.sidebar.title("Navigation")
selection = st.sidebar.radio("Go to", ["Dashboard", "Stage 1: Sentiment Polarity Analysis", "Stage 2: Emotion Mood-tag Analysis", "Stage 3: Text Transformation & Normalization"])
if selection == "Dashboard":
show_dashboard()
elif selection == "Stage 1: Sentiment Polarity Analysis":
show_sentiment_analysis()
elif selection == "Stage 2: Emotion Mood-tag Analysis":
# show_emotion_analysis()
st.write("This section is under development.")
elif selection == "Stage 3: Text Transformation & Normalization":
# show_text_transformation()
st.write("This section is under development.")
st.sidebar.title("About")
st.sidebar.info("""
**Contributors:**
- Archisman Karmakar
- [LinkedIn](https://www.linkedin.com/in/archismankarmakar/)
- [GitHub](https://www.github.com/ArchismanKarmakar)
- [Kaggle](https://www.kaggle.com/archismancoder)
- Sumon Chatterjee
- [LinkedIn](https://www.linkedin.com/in/sumon-chatterjee-3b3b43227)
- [GitHub](https://github.com/Sumon670)
- [Kaggle](https://www.kaggle.com/sumonchatterjee)
**Mentors:**
- Prof. Anupam Mondal
- [LinkedIn](https://www.linkedin.com/in/anupam-mondal-ph-d-8a7a1a39/)
- [Google Scholar](https://scholar.google.com/citations?user=ESRR9o4AAAAJ&hl=en)
- [Website](https://sites.google.com/view/anupammondal/home)
- Prof. Sainik Kumar Mahata
- [LinkedIn](https://www.linkedin.com/in/mahatasainikk)
- [Google Scholar](https://scholar.google.co.in/citations?user=OcJDM50AAAAJ&hl=en)
- [Website](https://sites.google.com/view/sainik-kumar-mahata/home)
This is our research project for our B.Tech final year and a journal which is yet to be published.
""")
if __name__ == "__main__":
main()