Debugging code in app.py.

app.py

@@ -10,14 +10,11 @@ nltk.download('stopwords')
 from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.feature_extraction.text import TfidfVectorizer
 
-from transformers import pipeline
-
 # file name
-#lr_filename = 'logistic_regression.pkl'
-model = pipeline("sentiment-analysis", model="michellejieli/NSFW_text_classifier")
+lr_filename = 'logistic_regression.pkl'
 
 # Load model from pickle file
-# model = pickle.load(open(lr_filename, 'rb'))
+model = pickle.load(open(lr_filename, 'rb'))
 
 
 # Process input text, including removing stopwords, converting to lowercase, and removing punctuation
@@ -40,7 +37,7 @@ def vectorize_text(text):
 
 def predict(text):
     text = vectorize_text(text)
-    prediction = model.predict(text).tostring()
+    prediction = model.predict(text)
     return prediction