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import streamlit as st | |
from transformers import pipeline | |
# Load Hugging Face model | |
model_name = "distilbert-base-uncased-finetuned-sst-2-english" | |
classifier = pipeline("sentiment-analysis", model=model_name) | |
# Streamlit UI | |
st.title("🤖 Sentiment Analysis App") | |
st.write("Enter some English text below to analyze sentiment.") | |
user_input = st.text_area("Text input", height=150) | |
if st.button("Predict"): | |
if user_input.strip() == "": | |
st.warning("Please enter some text.") | |
else: | |
with st.spinner("Analyzing..."): | |
result = classifier(user_input)[0] | |
st.success(f"**Label**: {result['label']} \n**Confidence**: {result['score']:.4f}") | |