Load prediction model and update Streamlit app interface

app.py

@@ -1,16 +1,12 @@
 import streamlit as st
+from utils.prediction import load_model_for_prediction
 #import transformers
 #from transformers import pipeline
 
 st.title('My first app')
 x = st.slider('Select a value')
 st.write(x, 'squared is', x * x)
+# load the model and cache it
+model, label_encoder, tokenizer = load_model_for_prediction()
+st.write('Model loaded')
 
-# classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
-
-# # Example input text
-# input_text = "I love using Hugging Face models!"
-
-# # Get the classification result
-# result = classifier(input_text)
-# st.write(result)