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app.py

@@ -19,10 +19,6 @@ FEATURE_COLS = [
 # Caching Function to Load Model and Scaler
 @st.cache_resource
 def load_artifacts():
-    """
-    Downloads and loads the model and scaler from the Hugging Face Hub.
-    The @st.cache_resource decorator ensures this function only runs once.
-    """
     try:
         with st.spinner("Downloading and loading model artifacts..."):
             # Download and load the model
@@ -50,12 +46,10 @@ st.set_page_config(
 
 st.title("Predict Engine Condition")
 st.markdown(
-    "Use the sliders below to input the current engine sensor readings and predict "
-    "if the engine is running **NORMAL (0)** or requires **IMMEDIATE MAINTENANCE (1)**. "
-    "This model uses a pre-trained Random Forest classifier."
+    "This model forecasts potential engine failures, classifying the status as **Normal (0)** or requiring **Immediate Maintenance (1)**."
 )
 st.markdown(
-    "**Note:** The slider ranges are based on the minimum and maximum values observed in the training dataset"
+    "**Note:** Adjust the sliders below with current sensor readings to check the engine condition."
 )
 
 if model is None or scaler is None: