code: def __init__(self, **kwargs):
      self.set_common = None
      if False:
          common_words_file = "data/NGSL_1.2_stats.csv.zip"
          if os.path.isfile(common_words_file):
              df = pd.read_csv(common_words_file)
              self.set_common = set(df["Lemma"].values.tolist())
      else:
          # https://norvig.com/ngrams/count_1w.txt
          common_words_file = "data/count_1w.txt.zip"
          if os.path.isfile(common_words_file):
              df = pd.read_csv(
                  common_words_file,
                  names=["word", "freq"],
                  header=None,
                  sep="\t",
              )
              df = df.head(1000)
              self.set_common = set(df["word"].values.tolist())
              for k in list(string.ascii_lowercase):
                  keep = {"i", "I", "A", "a"}
                  if k in self.set_common:
                      if k in keep:
                          continue
                      self.set_common.remove(k)
  
      super().__init__(**kwargs)
  
file_path: h2ogpt/metrics/quip.py
imports: import os
  import datasets
  import pandas
  import sacrebleu
  from packaging import version
  from sacrebleu import CHRF
  import string
  import evaluate
label_desc: Use image node_id 1 to create a new Quip object from inherited base classes: evaluate with example: obj = Quip()