code: def get_config(run_local: str = "") -> ml_collections.ConfigDict:
      """Returns the experiment configuration."""
      config = base_clip_clip.get_config(run_local)
  
      config.experiment_name = "clip_bert"
  
      config.model.text_encoder_name = "bert"
      config.model.text_encoder = ml_collections.ConfigDict()
      config.model.text_encoder.config_name = "base"
  
      config.dataset_configs.vocab_size = 30_522
      # TODO(sacastro): try cased. We'd need to change the DMVR BertTokenizer.
      config.dataset_configs.lowercase = True
  
      # The following configurations are meant to be used by DMVR datasets but also
      # as input to other parts of the config.
  
      config.dataset_configs.tokenizer.tokenizer_type = "bert"
  
      # Add vocab path.
      config.dataset_configs.tokenizer.tokenizer_vocab = ""
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(run_local) and returns: config