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import streamlit as st | |
from setfit import SetFitModel | |
def load_model(): | |
st.write("Loading model...") | |
return SetFitModel.from_pretrained("Tryfonas/setfit-paraphrase-mpnet-base-v2-sst2") | |
try: | |
model = load_model() | |
st.write("Model loaded successfully!") | |
except Exception as e: | |
st.error(f"Failed to load model: {e}") | |
st.title("Text Sentiment Analysis ππ") | |
user_input = st.text_input("Enter a sentence for sentiment analysis:", placeholder="I love this!") | |
if st.button("Analyze Sentiment"): | |
if user_input: | |
try: | |
predictions = model([user_input]) | |
st.write(f"Prediction: {predictions[0]}") | |
except Exception as e: | |
st.error(f"Error during prediction: {e}") | |
else: | |
st.write("Please enter a sentence to analyze.") | |