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_t5"
  
      config.model.text_encoder_name = "t5"
      config.model.text_encoder = ml_collections.ConfigDict()
      config.model.text_encoder.config_name = "base"
  
      # 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 = "t5"
  
      config.dataset_configs.tokenizer.tokenizer_vocab = "gs://t5-data/vocabs/cc_all.32000.100extra/sentencepiece.model"
      config.dataset_configs.tokenizer.prepend_bos = False
  
      config.dataset_configs.tokenizer_type = "sentence_piece"
      config.dataset_configs.vocab_size = 32_128
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(run_local) and returns: config