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 init_spec(cls) -> lit_model.Spec:
      return {
          "model_name_or_path": lit_types.String(
              default="bert-base-uncased"
          ),
          "top_k": lit_types.Integer(default=10, min_val=1, max_val=25),
      }
  
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 2 for calling the BertMLM obj's underlying member method code with example usage: obj.init_spec(cls) and returns: dict