---
license: apache-2.0
---
### Inference Code
```Python
import numpy as np
import pickle
from keras.preprocessing.sequence import pad_sequences
from keras.models import load_model

def predict_word(seed_text: str, tokenizer, model, next_words: int = 2) -> str:
    for _ in range(next_words):
        token_list = tokenizer.texts_to_sequences([seed_text])[0]
        token_list = pad_sequences([token_list], maxlen=max_sequence_len-1, padding='pre')
        predicted = np.argmax(model.predict(token_list), axis=-1)
        output_word = ""
        for word, index in tokenizer.word_index.items():
            if index == predicted:
                output_word = word
                break
        seed_text += " " + output_word
    return seed_text
```