class_docstr: Determines which few-shot examples to use when sampling explanations.
class_docstr_tok: ["Determines","which","few-shot","examples","to","use","when","sampling","explanations","."]
code: def from_string(cls, string: str) -> FewShotExampleSet:
      for example_set in FewShotExampleSet:
          if example_set.value == string:
              return example_set
      raise ValueError(f"Unrecognized example set: {string}")
  
file_path: automated-interpretability/neuron-explainer/neuron_explainer/explanations/few_shot_examples.py
imports: from __future__ import annotations
  from dataclasses import dataclass
  from enum import Enum
  from typing import List, Optional
  from neuron_explainer.activations.activations import ActivationRecord
  from neuron_explainer.fast_dataclasses import FastDataclass
label_desc: Use image node_id 1 for calling the FewShotExampleSet obj's underlying member method code with example usage: obj.from_string(cls, string) and returns: example_set