model size expected (none,30) found (none,200).

app.py

@@ -51,7 +51,7 @@ def get_sentiment(text):
     text = [stemmer.lemmatize(word) for word in text]
     text = ' '.join(text)
     text = tokenizer.texts_to_sequences([text])[0]
-    text += [0] * (200 - len(text))
+    text += [0] * (30 - len(text))
     text = np.array(text).reshape(-1, 200)
     x = model.predict(text).tolist()[0][0]
     return ('Positive' if x >= 0.5 else 'negative') + ' sentiment!'