Minor error

app.py

@@ -51,17 +51,17 @@ if uploaded_file is not None:
 
     # Load the selected model
     if model_name == "K-Nearest Neighbors - (Single Label)":
-        model = joblib.load("../models/knn.pkl")
+        model = joblib.load("./models/knn.pkl")
     elif model_name == "Logistic Regression - (Single Label)":
-        model = joblib.load("../models/logistic.pkl")
+        model = joblib.load("./models/logistic.pkl")
     elif model_name == "Support Vector Machines - (Single Label)":
-        model = joblib.load("../models/svm.pkl")
+        model = joblib.load("./models/svm.pkl")
     elif model_name == "Neural Network - (Single Label)":
-        model = joblib.load("../models/nn.pkl")
+        model = joblib.load("./models/nn.pkl")
     elif model_name == "XGB Classifier - (Single Label)":
-        model = joblib.load("../models/xgb.pkl")
+        model = joblib.load("./models/xgb.pkl")
     elif model_name == "XGB - (Multi Label)":
-        model = joblib.load("../models/xgb_mlb.pkl")
+        model = joblib.load("./models/xgb_mlb.pkl")
     elif model_name == "Convolutional Recurrent Neural Network - (Multi Label)":
         model = tensorflow.keras.models.load_model("../models/model_crnn1.h5", compile=False)
         model.compile(loss=binary_crossentropy,
@@ -136,4 +136,4 @@ if uploaded_file is not None:
     else:
         predicted_label = model.predict(features)[0]
         st.write(f"Predicted Genre: {predicted_label}")
-        st.metric("Predicted Genre:",{predicted_label})
+        st.metric("Predicted Genre:",str(predicted_label))