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import streamlit as st |
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from app_models.rubert_MODEL import classify_text |
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from app_models.bag_of_words_MODEL import predict |
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from app_models.lstm_MODEL import predict_review |
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class_prefix = 'This review is likely...' |
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def run(): |
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st.title("Movie Review Classification") |
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st.write("This page will compare three models: Bag of Words/TF-IDF, LSTM, and BERT.") |
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user_input = st.text_area("") |
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if st.button('Classify with BoW/TF-IDF'): |
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st.write(f'{class_prefix}{predict(user_input)}') |
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if st.button('Classify with LSTM'): |
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st.write(f'{class_prefix}{predict_review(user_input)}') |
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if st.button('Classify with ruBERT'): |
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st.write(f'{class_prefix}{classify_text(user_input)}') |