code: def load_model(bento_model: str | Tag | Model) -> ModelType:
      """
      Load the picklable model with the given tag from the local BentoML model store.
  
      Args:
          bento_model: Either the tag of the model to get from the store,
                       or a BentoML :class:`~bentoml.Model` instance to load
                       the model from.
  
      Returns:
          The picklable model loaded from the model store or BentoML :obj:`~bentoml.Model`.
  
      Example:
  
      .. code-block:: python
  
          import bentoml
  
          picklable_model = bentoml.picklable_model.load_model('my_model:latest')
      """  # noqa
      if not isinstance(bento_model, Model):
          bento_model = get(bento_model)
  
      if bento_model.info.module not in (MODULE_NAME, __name__):
          raise NotFound(
              f"Model {bento_model.tag} was saved with module {bento_model.info.module}, not loading with {MODULE_NAME}."
          )
  
      model_file = bento_model.path_of(f"{SAVE_NAMESPACE}{PKL_EXT}")
  
      with open(model_file, "rb") as f:
          # The protocol version used is detected automatically, so we do not
          # have to specify it.
          return cloudpickle.load(f)
  
file_path: BentoML/grpc-client/bentoml/_internal/frameworks/picklable.py
imports: from __future__ import annotations
  import logging
  import typing
  from types import ModuleType
  from typing import TYPE_CHECKING
  import cloudpickle
  import bentoml
  from bentoml import Tag
  from bentoml.exceptions import NotFound
  from bentoml.models import Model
  from bentoml.models import ModelContext
  from ..models import PKL_EXT
  from ..models import SAVE_NAMESPACE
  from ..models.model import ModelSignature
  from ..models.model import PartialKwargsModelOptions
label_desc: Use image node_id 2 for calling a global function with example usage: load_model(bento_model) and returns: cloudpickle