src/streamlit_app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

# Load model and tokenizer
model_name = "prd101-wd/phi1_5-sentiment-merged"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Create a pipeline
classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

# Streamlit UI
st.title("Sentiment Classifier")

text = st.text_area("Enter text to classify:")

if st.button("Classify"):
    if text.strip():
        result = classifier(text)[0]
        st.markdown(f"**Label:** {result['label']}  \n**Score:** {result['score']:.4f}")
    else:
        st.warning("Please enter some text.")