class_docstr: ModuleWrapperBase around a model object to enable serving at scale.
  
  Create a ``Servable`` from either (LM, LOCATION) or (LOCATION,)
  
  Parameters
  ----------
  *args
      A model class and path to the asset file (url or local file path) OR
      a singular path to a torchscript asset which can be loaded without the
      model class definition.
  download_path
      Optional url to download a model from.
  
  TODO
  ----
  *  How to handle ``__init__`` args for ``torch.nn.Module``
  *  How to handle ``__init__`` args not recorded in hparams of ``pl.LightningModule``
class_docstr_tok: ["ModuleWrapperBase","around","a","model","object","to","enable","serving","at","scale",".","Create","a","``","Servable","``","from","either","(","LM",",","LOCATION",")","or","(","LOCATION",",",")","Parameters","--","--","--","--","--","*","args","A","model","class","and","path","to","the","asset","file","(","url","or","local","file","path",")","OR","a","singular","path","to","a","torchscript","asset","which","can","be","loaded","without","the","model","class","definition",".","download_path","Optional","url","to","download","a","model","from",".","TODO","--","--","*","How","to","handle","``","__init__","``","args","for","``","torch.nn.Module","``","*","How","to","handle","``","__init__","``","args","not","recorded","in","hparams","of","``","pl.LightningModule","``"]
code: def __repr__(self):
      return repr(self.instance)
  
imports: import dataclasses
  from dataclasses import dataclass, field, make_dataclass
  from pathlib import Path
  from typing import Dict, Iterator, List, NamedTuple, Optional, Tuple, Type, TypeVar, Union
  import pytorch_lightning
  import torch
  from flash.core.serve.types.base import BaseType
  from flash.core.serve.utils import download_file
  from flash.core.utilities.imports import _PYDANTIC_AVAILABLE, requires
label_desc: Use image node_id 3 for calling the Servable obj's underlying member method code with example usage: obj.__repr__() and returns: repr