code: def run_server(load_path: str):
      """Run a LIT server with the trained coreference model."""
      # Normally path is a directory; if it's an archive file, download and
      # extract to the transformers cache.
      if load_path.endswith(".tar.gz"):
          load_path = file_cache.cached_path(
              load_path, extract_compressed_file=True
          )
      # Load model from disk.
      full_model = model.FrozenEncoderCoref.from_saved(
          load_path,
          encoder_cls=encoders.BertEncoderWithOffsets,
          classifier_cls=edge_predictor.SingleEdgePredictor,
      )
  
      # Set up the LIT server.
      models = {"model": full_model}
      datasets = {"winogender": winogender.WinogenderDataset()}
      if _ONTONOTES_EDGEPROBE_PATH.value:
          datasets["ontonotes_dev"] = ontonotes.OntonotesCorefDataset(
              os.path.join(
                  FLAGS.ontonotes_edgeprobe_path, "development.json"
              )
          )
      # Start the LIT server. See server_flags.py for server options.
      lit_demo = dev_server.Server(
          models,
          datasets,
          layouts=CUSTOM_LAYOUTS,
          **server_flags.get_flags(),
      )
      return lit_demo.serve()
  
imports: from collections.abc import Sequence
  import os
  import sys
  from typing import Optional
  from absl import app
  from absl import flags
  from absl import logging
  from lit_nlp import dev_server
  from lit_nlp import server_flags
  from lit_nlp.api import dataset
  from lit_nlp.api import dtypes
  from lit_nlp.api import layout
  from lit_nlp.api import types
  from lit_nlp.examples.coref import edge_predictor
  from lit_nlp.examples.coref import encoders
  from lit_nlp.examples.coref import model
  from lit_nlp.examples.coref.datasets import ontonotes
  from lit_nlp.examples.coref.datasets import winogender
  from lit_nlp.lib import file_cache
  from lit_nlp.lib import utils
label_desc: Use image node_id 4 for calling a global function with example usage: run_server(load_path) and returns: lit_demo