class_docstr: Question Answering Jax model based on TyDiQA Dataset.
code: def __init__(
      self,
      model_name: str,
      model=None,
      tokenizer=None,
      **unused_kw,
  ):
      super().__init__()
      self.tokenizer = tokenizer or _BertTokenizer.from_pretrained(
          model_name
      )
      self.model = (
          model
          or _FlaxBertForQuestionAnswering.from_pretrained(model_name)
      )
  
file_path: lit/lit_nlp/examples/models/tydi.py
imports: from collections.abc import Iterable
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.datasets import question_answering
  import numpy
  import transformers
label_desc: Use image node_id 1 to create a new TyDiModel object from inherited base classes: lit_model with example: obj = TyDiModel(model_name, model, tokenizer)