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app.py
Browse files
app.py
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import streamlit as st
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from transformers import pipeline
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st.title('Sentiment Analysis App')
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text = st.text_input(' ')
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mname = st.selectbox(
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'Select a pre-trained model',
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['distilbert-base-uncased', 'distilbert-base-cased', 'bert-base-uncased', 'bert-base-cased',
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'cardiffnlp/twitter-roberta-base-sentiment-latest',
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'cardiffnlp/twitter-xlm-roberta-base-sentiment',
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'j-hartmann/emotion-english-distilroberta-base',
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'ProsusAI/finbert'
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]
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)
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if st.button('Analyze Sentiment'):
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model = pipeline('sentiment-analysis', model=mname)
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result = model(text)[0]
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st.write(f'Sentiment: {result["label"]}')
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st.write(f'Score: {result["score"]}')
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