load_embedding_network.py

#This code is a cheap adaptation of example code from tf's hub website:
# More at: https://tfhub.dev/google/universal-sentence-encoder-multilingual/1

#Initialize tf graph:
g = tf.Graph()
with g.as_default():
  text_input = tf.placeholder(dtype=tf.string, shape=[None])
  #Here you can specify your path
  embed = hub.Module('/path/to/model/')
  #Or downlload it directly from tf's hub:
  # embed = hub.Module("https://tfhub.dev/google/universal-sentence-encoder-multilingual/1")
  embedded_text = embed(text_input)
  init_op = tf.group([tf.global_variables_initializer(), tf.tables_initializer()])
g.finalize()

# Initialize session.
session = tf.Session(graph=g)
session.run(init_op)