Upload app.py

app.py

@@ -5,13 +5,15 @@ import tensorflow as tf
 import numpy as np
 from tensorflow.keras.layers import TextVectorization
 
+df = pd.read_csv(os.path.join('train.csv'))
+X = df['comment_text']
 
 columns = ['toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
 
-# load numpy array from npy file
-from numpy import load
-# load array
-xValues = np.load('forVectorizer.npy', allow_pickle=True)
+# # load numpy array from npy file
+# from numpy import load
+# # load array
+# xValues = np.load('forVectorizer.npy', allow_pickle=True)
 
 # SET THE VECTORIZER    
 #set max features
@@ -20,7 +22,7 @@ vectorizer = TextVectorization(max_tokens=MAX_FEATURES,
                               output_sequence_length=1800,
                               output_mode='int')
 
-vectorizer.adapt(xValues)
+vectorizer.adapt(X.values)
 
 model = tf.keras.models.load_model('toxicity.h5')