[UPD] app.py

app.py

@@ -4,17 +4,14 @@ import numpy as np
 import pickle
 import IPython.display as ipd
 from sklearn.preprocessing import LabelEncoder
+from tensorflow.keras.models import load_model
 
 
 model_path = 'model/audio_prediction_model.pkl'
 
 le = LabelEncoder()
 
-with open(model_path, 'rb') as model_file:
-    try:
-        model = pickle.load(model_file)
-    except Exception as e:
-        st.error(f"Erreur lors du chargement du modèle : {e}")
+model = load_model('model/audio_prediction_model.h5')
 
 
 def prediction_audio(audiofile, model):