class_docstr: Basic class for a `Learner` in NLP.
class_docstr_tok: ["Basic","class","for","a","`","Learner","`","in","NLP","."]
code: def __init__(
      self,
      dls: DataLoaders,  # Text `DataLoaders`
      model,  # A standard PyTorch model
      alpha: float = 2.0,  # Param for `RNNRegularizer`
      beta: float = 1.0,  # Param for `RNNRegularizer`
      moms: tuple = (
          0.8,
          0.7,
          0.8,
      ),  # Momentum for `Cosine Annealing Scheduler`
      **kwargs,
  ):
      super().__init__(dls, model, moms=moms, **kwargs)
      self.add_cbs(rnn_cbs())
  
imports: from __future__ import annotations
  from ..basics import *
  from .core import *
  from .data import *
  from .models.core import *
  from .models.awdlstm import *
  from ..callback.rnn import *
  from ..callback.progress import *
  from .models.core import _model_meta
label_desc: Use image node_id 1 to create a new TextLearner object from inherited base classes: Learner with example: obj = TextLearner(dls, model, alpha, beta, moms)