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app.py

@@ -4,8 +4,8 @@ import joblib
 # from sklearn.feature_extraction.text import TfidfVectorizer
 
 # Load your trained model and vectorizer (assuming they're saved as 'lgbm_model.pkl' and 'vectorizer.pkl')
-model = joblib.load('lgbm_model.pkl')
-vectorizer = joblib.load('vectorizer.pkl')
+model = joblib.load('lgbm_model.joblib')
+vectorizer = joblib.load('vectorizer.joblib')
 
 def classify_text(text):
     # Transform the input text using the loaded vectorizer

lgbm_model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a1b1e38213610b83c26e8ecca7306b5598b04b471c2253530d13b3ff52715db8
+size 2207924

vectorizer.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ffde94fdae46050354244414d5b546e62393226a671057d83da2ccbabda59495
+size 304927