fifth

pages/7_NEXT_WORD_PREDICTOR.py

@@ -40,6 +40,7 @@ if st.button("PREDICT"):
 
 
     max_len = max([len(x) for x in input_sequences])
+    use = max_len-1
 
     padded_input_sentences = pad_sequences(input_sequences , maxlen = max_len , padding ="pre")
     X = padded_input_sentences[:,:-1]
@@ -50,7 +51,7 @@ if st.button("PREDICT"):
 
 
     model = Sequential()
-    model.add(Embedding(num_class+1,100,input_length = 99))
+    model.add(Embedding(num_class+1,100,input_length = use))
 
     model.add(LSTM(250))
     
@@ -65,7 +66,7 @@ if st.button("PREDICT"):
     
 
         output_token = tokenizer.texts_to_sequences([test])[0]
-        padded_token = pad_sequences([output_token] , maxlen=99, padding="pre")
+        padded_token = pad_sequences([output_token] , maxlen=max_len, padding="pre")
         output = np.argmax(model.predict(padded_token))
         for word,index in tokenizer.word_index.items():
             if index == output: