class_docstr: Uses the underlying FoundationCache, but hiding the transformer.
  
  Useful for when loading a downstream model such as POS which has a
  finetuned transformer, and we don't want the transformer reused
  since it will then have the finetuned weights for other models
  which don't want them
code: def load_bert(self, transformer_name):
      return load_bert(transformer_name)
  
file_path: stanza/stanza/models/common/foundation_cache.py
imports: import logging
  import threading
  from stanza.models.common import bert_embedding
  from stanza.models.common.char_model import CharacterLanguageModel
  from stanza.models.common.pretrain import Pretrain
label_desc: Use image node_id 1 for calling the NoTransformerFoundationCache obj's underlying member method code with example usage: obj.load_bert(transformer_name) and returns: load_bert