class_docstr: BERT masked LM using Huggingface Transformers and TensorFlow 2.
class_docstr_tok: ["BERT","masked","LM","using","Huggingface","Transformers","and","TensorFlow","2","."]
code: def max_minibatch_size(self) -> int:
      # The lit.Model base class handles batching automatically in the
      # implementation of predict(), and uses this value as the batch size.
      return 8
  
imports: import re
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.models import model_utils
  from lit_nlp.lib import file_cache
  from lit_nlp.lib import utils
  import numpy
  import tensorflow
  import transformers
label_desc: Use image node_id 6 for calling the BertMLM obj's underlying member method code with example usage: obj.max_minibatch_size() and returns: int