class_docstr: A Language Model for Finetune
  
  :param config: A :py:class:`finetune.config.Settings` object or None (for default config).
  :param \**kwargs: key-value pairs of config items to override.
class_docstr_tok: ["A","Language","Model","for","Finetune",":","param","config",":","A",":","py",":","class",":","`","finetune.config.Settings","`","object","or","None","(","for","default","config",")",".",":","param","\\","*","*","kwargs",":","key-value","pairs","of","config","items","to","override","."]
docstr: :param X: list or array of text.
  :param Y: Not used.
  :param batch_size: integer number of examples per batch. When N_GPUS > 1, this number
                     corresponds to the number of training examples provided to each GPU.
docstr_tok: [":","param","X",":","list","or","array","of","text",".",":","param","Y",":","Not","used",".",":","param","batch_size",":","integer","number","of","examples","per","batch",".","When","N_GPUS",">","1",",","this","number","corresponds","to","the","number","of","training","examples","provided","to","each","GPU","."]
code: def finetune(
      self, X, Y=None, batch_size=None, context=None, **kwargs
  ):
      """
      :param X: list or array of text.
      :param Y: Not used.
      :param batch_size: integer number of examples per batch. When N_GPUS > 1, this number
                         corresponds to the number of training examples provided to each GPU.
      """
      if Y:
          raise ValueError(
              "No targets should be provided for the language model"
          )
      return super().finetune(
          X, Y=None, batch_size=batch_size, **kwargs
      )
  
imports: from finetune.base import PredictMode
  from finetune.target_models.classifier import Classifier
label_desc: Use image node_id 3 for calling the LanguageModel obj's underlying member method code with example usage: obj.finetune(X, Y, batch_size, context) and returns: super