Model from the Keras tutorial: https://keras.io/examples/nlp/bidirectional_lstm_imdb/

nlp_datasets_model.py

import numpy as np
from tensorflow import keras
from tensorflow.keras import layers

max_features = 20000  # Only consider the top 20k words
maxlen = 200  # Only consider the first 200 words of each movie review

def get_model():
    # Input for variable-length sequences of integers
    inputs = keras.Input(shape=(None,), dtype="int32")
    # Embed each integer in a 128-dimensional vector
    x = layers.Embedding(max_features, 128)(inputs)
    # Add 2 bidirectional LSTMs
    x = layers.Bidirectional(layers.LSTM(64, return_sequences=True))(x)
    x = layers.Bidirectional(layers.LSTM(64))(x)
    # Add a classifier
    outputs = layers.Dense(1, activation="sigmoid")(x)
    model = keras.Model(inputs, outputs)
    return model

model = get_model()
model.summary()