code: def num_examples_validator(df: pd.DataFrame) -> Remediation:
      """
      This validator will only print out the number of examples and recommend to the user to increase the number of examples if less than 100.
      """
      MIN_EXAMPLES = 100
      optional_suggestion = (
          ""
          if len(df) >= MIN_EXAMPLES
          else ". In general, we recommend having at least a few hundred examples. We've found that performance tends to linearly increase for every doubling of the number of examples"
      )
      immediate_msg = f"\n- Your file contains {len(df)} prompt-completion pairs{optional_suggestion}"
      return Remediation(
          name="num_examples", immediate_msg=immediate_msg
      )
  
imports: from __future__ import annotations
  import os
  import sys
  from typing import Any, TypeVar, Callable, Optional, NamedTuple
  from typing_extensions import TypeAlias
  from .._extras import pandas
label_desc: Use image node_id 1 for calling a global function with example usage: num_examples_validator(df) and returns: Remediation