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import streamlit as st | |
from transformers import pipeline | |
# Load the sentiment analysis model from Hugging Face | |
classifier = pipeline('sentiment-analysis') | |
# Create a Streamlit app | |
st.title('Sentiment Analysis with Hugging Face') | |
st.write('Enter some text and we will predict its sentiment!') | |
# Add a text input box for the user to enter text | |
text_input = st.text_input('Enter text here') | |
# When the user submits text, run the sentiment analysis model on it | |
if st.button('Submit'): | |
# Predict the sentiment of the text using the Hugging Face model | |
sentiment = classifier(text_input)[0]['label'] | |
# Display the sentiment prediction to the user | |
st.write(f'Sentiment: {sentiment}') | |