Updated v3 BERT model from https://tfhub.dev/tensorflow/bert_en_uncased_L-12_H-768_A-12/3

BERT_HUB_model_v3.py

import tensorflow_text as text  # Registers the ops.
import tensorflow as tf
import tensorflow_hub as hub

# text_input = ["This is a sample sentence."]
text_input = tf.keras.layers.Input(shape=(), dtype=tf.string)
preprocessor = hub.KerasLayer(
    "https://tfhub.dev/tensorflow/bert_en_uncased_preprocess/1")
encoder_inputs = preprocessor(text_input) # dict with keys: 'input_mask', 'input_type_ids', 'input_word_ids'
encoder = hub.KerasLayer(
    "https://tfhub.dev/tensorflow/bert_en_uncased_L-12_H-768_A-12/3",
    trainable=True)
outputs = encoder(encoder_inputs)
pooled_output = outputs["pooled_output"]      # [batch_size, 768].
sequence_output = outputs["sequence_output"]  # [batch_size, seq_length, 768].