Keras, how do I predict after I trained a model?

Question

I\'m playing with the reuters-example dataset and it runs fine (my model is trained). I read about how to save a model, so I could load it later to use again. But how do I

Answer 1

Your can use your tokenizer and pad sequencing for a new piece of text. This is followed by model prediction. This will return the prediction as a numpy array plus the label itself.

For example:

new_complaint = ['Your service is not good']
seq = tokenizer.texts_to_sequences(new_complaint)
padded = pad_sequences(seq, maxlen=maxlen)
pred = model.predict(padded)
print(pred, labels[np.argmax(pred)])