code: def get_config(run_local: str = "") -> ml_collections.ConfigDict:
      """Returns the experiment configuration."""
      config = mixin_bit.get_config(run_local)
  
      config.trainer_name = "zero_shot_classification_trainer"
  
      config.dataset_canonical_name = "imagenet"
  
      config.dataset_configs.dataset = "imagenet2012:5.*.*"
      config.dataset_configs.text_out_key = "label"
  
      config.dataset_configs.train_split_name = "train"
      config.dataset_configs.train_split_start = ""
      config.dataset_configs.train_split_end = "100%"
  
      config.dataset_configs.val_split_name = "validation"
      config.dataset_configs.val_split_start = ""
      config.dataset_configs.val_split_end = (
          "4" if run_local else "100%"
      )
  
      config.dataset_configs.tokenizer_type = ""
      config.dataset_configs.is_classification = True
  
      config.dataset_configs.class_names = CLASS_NAMES
  
      config.class_templates = (
          ["{}"] if run_local else base_clip.CLIP_IMAGENET_TEMPLATES
      )
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(run_local) and returns: config