code: def predict(self, text, tables, model_path=None, **kwargs):
      # Please don't use this in production
      # it's just a shim for predict_from_file so we don't have 2 separate predict implementations.
      scheduler = Scheduler()
      with tempfile.TemporaryDirectory() as tmpdir:
          model_path = model_path or os.path.join(
              tmpdir, "table_model.jl"
          )
          self.save(model_path)
          return self.predict_from_file(
              text=text,
              tables=tables,
              model_file_path=model_path,
              scheduler=scheduler,
              **kwargs,
          )
  
imports: import copy
  import functools
  import os
  import tempfile
  import typing
  import sys
  from finetune.base_models import TableRoBERTa
  from finetune.util.metrics import sequences_overlap
  from finetune.scheduler import Scheduler
  from finetune.encoding.input_encoder import BaseEncoder
  from finetune import SequenceLabeler
label_desc: Use image node_id 4 for calling the TableLabeler obj's underlying member method code with example usage: obj.predict(text, tables, model_path) and returns: self