Update src/streamlit_app.py

src/streamlit_app.py

@@ -67,7 +67,13 @@ def text_preprocessing(text):
   text = ' '.join(tokens)
 
   return text
-
+    
+hub_layer = tf_hub.KerasLayer(
+    "https://www.kaggle.com/models/google/nnlm/TensorFlow2/id-dim128-with-normalization/1",
+    input_shape=[],
+    dtype=tf.string,
+    trainable=False
+)
 # Define the Streamlit interface
 st.title('Sentiment Analysis App')
 
@@ -78,7 +84,8 @@ if st.button('Analyze'):
     if user_input:
         # Preprocess the input text
         processed_text = text_preprocessing(user_input)
-        prediction = model.predict([[processed_text]])
+        data_inf = hub_layer(processed_text) 
+        prediction = model.predict(data_inf)
         sentiment = "Positive" if prediction[0] > 0.5 else "Negative"
 
         # Display the result