class_docstr: A model wrapper queries a model with a list of text inputs.
  
  Classification-based models return a list of lists, where each sublist
  represents the model's scores for a given input.
  
  Text-to-text models return a list of strings, where each string is the
  output – like a translation or summarization – for a given input.
class_docstr_tok: ["A","model","wrapper","queries","a","model","with","a","list","of","text","inputs",".","Classification-based","models","return","a","list","of","lists",",","where","each","sublist","represents","the","model","'s","scores","for","a","given","input",".","Text-to-text","models","return","a","list","of","strings",",","where","each","string","is","the","output","\u2013","like","a","translation","or","summarization","\u2013","for","a","given","input","."]
docstr: Prepare model input ids and get model predict output.
  
  *inputs
      1、attack supported tasks(1/2 text string)
      2、other tasks(original sample content)
  
  Returns:
      1、attack supported tasks(label scores)
      2、other tasks(label ids)
  
  :param tuple inputs: list of original text
  :return: numpy.ndarray
docstr_tok: ["Prepare","model","input","ids","and","get","model","predict","output",".","*","inputs","1\u3001attack","supported","tasks","(","1\/2","text","string",")","2\u3001other","tasks","(","original","sample","content",")","Returns",":","1\u3001attack","supported","tasks","(","label","scores",")","2\u3001other","tasks","(","label","ids",")",":","param","tuple","inputs",":","list","of","original","text",":","return",":","numpy.ndarray"]
code: def __call__(self, *inputs):
      r"""
      Prepare model input ids and get model predict output.
  
      *inputs
          1、attack supported tasks(1/2 text string)
          2、other tasks(original sample content)
  
      Returns:
          1、attack supported tasks(label scores)
          2、other tasks(label ids)
  
      :param tuple inputs: list of original text
      :return: numpy.ndarray
      """
      raise NotImplementedError()
  
file_path: textflint/textflint/input/model/flint_model/flint_model.py
imports: from abc import ABC
  import numpy
  from ..metrics.metrics import accuracy_score
  from ..metrics.metrics import POSMetric
  from ..metrics.nerspanmetric import NERSpanMetric
label_desc: Use image node_id 4 for calling the FlintModel obj's underlying member method code with example usage: obj.__call__() without return types