class_docstr: Custom GLUE model for the Input Salience Evaluation demo.
docstr: Initializes a custom SST-2 model for the Input Salience Eval demo.
  
  Args:
    model_name: The model's name. Used to determine dataset compatibility.
    *args: Additional positional args to pass to the SST2Model base class.
    **kw: Additional keyword args to pass to the SST2Model base class.
docstr_tok: ["Initializes","a","custom","SST-2","model","for","the","Input","Salience","Eval","demo",".","Args",":","model_name",":","The","model","'s","name",".","Used","to","determine","dataset","compatibility",".","*","args",":","Additional","positional","args","to","pass","to","the","SST2Model","base","class",".","*","*","kw",":","Additional","keyword","args","to","pass","to","the","SST2Model","base","class","."]
code: def __init__(self, model_name: str, *args, **kw):
      """Initializes a custom SST-2 model for the Input Salience Eval demo.
  
      Args:
        model_name: The model's name. Used to determine dataset compatibility.
        *args: Additional positional args to pass to the SST2Model base class.
        **kw: Additional keyword args to pass to the SST2Model base class.
      """
      super().__init__(*args, **kw)
      self._model_name = model_name
  
file_path: lit/lit_nlp/examples/is_eval/models.py
imports: from typing import cast
  from lit_nlp.api import dataset
  from lit_nlp.examples.is_eval import datasets
  from lit_nlp.examples.models import glue_models
label_desc: Use image node_id 1 to create a new ISEvalModel object from inherited base classes: glue_models with example: obj = ISEvalModel(model_name)