code: def few_shot_classification(presets: str = DEFAULT):
      """
      Register the presets for few_shot_classification.
  
      Parameters
      ----------
      presets
          The preset name.
  
      Returns
      -------
      hyperparameters
          The hyperparameters for a given preset.
      hyperparameter_tune_kwargs
          The hyperparameter tuning kwargs.
      """
      hyperparameters, hyperparameter_tune_kwargs = default(
          presets=presets
      )
      hyperparameters.update(
          {
              "model.hf_text.checkpoint_name": "sentence-transformers/all-mpnet-base-v2",
              "model.hf_text.pooling_mode": "mean",
              "model.names": ["hf_text", "clip"],
              "model.clip.checkpoint_name": "openai/clip-vit-large-patch14-336",
              "model.clip.image_size": 336,
              "env.eval_batch_size_ratio": 1,
          }
      )
      hyperparameter_tune_kwargs = {}
  
      return hyperparameters, hyperparameter_tune_kwargs
  
imports: from typing import List, Optional
  from autogluon.common.utils.try_import import try_import_ray
  from .constants import BEST_QUALITY, BINARY, DATA, DEFAULT, ENVIRONMENT, HIGH_QUALITY, MEDIUM_QUALITY, MODEL, MULTICLASS, OPTIMIZATION, REGRESSION
  from .registry import Registry
label_desc: Use image node_id 4 for calling a global function with example usage: few_shot_classification(presets) and returns: hyperparameters,  hyperparameter_tune_kwargs