class_docstr: BERT masked LM using Huggingface Transformers and TensorFlow 2.
class_docstr_tok: ["BERT","masked","LM","using","Huggingface","Transformers","and","TensorFlow","2","."]
docstr: Dynamically load a new BertMLM model given a model name.
docstr_tok: ["Dynamically","load","a","new","BertMLM","model","given","a","model","name","."]
code: def load(self, model_name_or_path):
      """Dynamically load a new BertMLM model given a model name."""
      return BertMLM(model_name_or_path, self.top_k)
  
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 8 for calling the BertMLM obj's underlying member method code with example usage: obj.load(model_name_or_path) and returns: BertMLM