AI, NLP, Deep Learning, Lstm, TensorFlow.
loss='categorical_crossentropy', metrics=['accuracy']) model_lstm.fit(X, y, epochs=100, verbose=0) # Generate text using the trained models def generate_text(seed_text, model, max_sequence_len, num_words): for _ in range(num_words): token_list = tokenizer.texts_to_sequences([seed_text])[0]