class_docstr: Cross-lingual NLI; see https://cims.nyu.edu/~sbowman/xnli/.
class_docstr_tok: ["Cross-lingual","NLI",";","see","https",":","\/\/cims.nyu.edu\/~sbowman\/xnli\/","."]
code: def __init__(self, split: str, languages=("en", "es", "hi", "zh")):
      self._examples = []
      for ex in load_tfds("xnli", split=split):
          # Each TFDS example contains all the translations; we unpack to individual
          # (premise, hypothesis) pairs that are compatible with a standard NLI
          # model.
          self._examples.extend(self._process_example(ex, languages))
  
imports: from typing import Optional
  from absl import logging
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  import pandas
  import tensorflow_datasets
label_desc: Use image node_id 2 to create a new XNLIData object from inherited base classes: lit_dataset with example: obj = XNLIData(split, languages)