def METHOD_NAME(text_file, sbert_model_to_load, batch_size=200):
    """
    Creates SBERT Embeddings from an input file
    """
    model = SentenceTransformer(sbert_model_to_load)
    with open(text_file, encoding="utf-8") as filino:
        train_text = list(map(lambda x: x, filino.readlines()))
    return np.array(model.encode(train_text, show_progress_bar=True, batch_size=batch_size))