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import streamlit as st | |
from transformers import pipeline | |
# Load the sentiment analysis model from Hugging Face | |
sentiment_analysis = pipeline("sentiment-analysis") | |
# Function to get sentiment prediction | |
def predict_sentiment(text): | |
result = sentiment_analysis(text) | |
label = result[0]['label'] | |
score = result[0]['score'] | |
return label, score | |
# Streamlit web app | |
def main(): | |
st.title("Sentiment Analysis App") | |
# Input text area | |
user_input = st.text_area("Enter text:", "Type or paste your text here...") | |
# Button to trigger sentiment prediction | |
if st.button("Predict Sentiment"): | |
# Display the result | |
sentiment_label, sentiment_score = predict_sentiment(user_input) | |
st.write(f"Sentiment: {sentiment_label}, Score: {sentiment_score:.4f}") | |
# Run the app | |
if __name__ == "__main__": | |
main() | |