code: def create(embedding_name, **kwargs):
      """Creates an instance of token embedding.
  
  
      Creates a token embedding instance by loading embedding vectors from an externally hosted
      pre-trained token embedding file, such as those of GloVe and FastText. To get all the valid
      `embedding_name` and `pretrained_file_name`, use
      `mxnet.contrib.text.embedding.get_pretrained_file_names()`.
  
  
      Parameters
      ----------
      embedding_name : str
          The token embedding name (case-insensitive).
  
  
      Returns
      -------
      An instance of `mxnet.contrib.text.glossary._TokenEmbedding`:
          A token embedding instance that loads embedding vectors from an externally hosted
          pre-trained token embedding file.
      """
  
      create_text_embedding = registry.get_create_func(
          _TokenEmbedding, "token embedding"
      )
      return create_text_embedding(embedding_name, **kwargs)
  
imports: import logging
  import os
  import tarfile
  import warnings
  import zipfile
  from .None import _constants
  from .None import vocab
  from ...None import ndarray
  from ...None import registry
  from ...None import base
  from ...util import is_np_array
  from ...None import numpy
  from ...None import numpy_extension
label_desc: Use image node_id 2 for calling a global function with example usage: create(embedding_name) and returns: create_text_embedding