class_docstr: Class which wraps a statsmodels estimation Results class and steps in to
  reattach metadata to results (if available)
docstr: Load a pickled results instance
  
  .. warning::
  
     Loading pickled models is not secure against erroneous or
     maliciously constructed data. Never unpickle data received from
     an untrusted or unauthenticated source.
  
  Parameters
  ----------
  fname : {str, handle}
      A string filename or a file handle.
  
  Returns
  -------
  Results
      The unpickled results instance.
docstr_tok: ["Load","a","pickled","results","instance","..","warning",":",":","Loading","pickled","models","is","not","secure","against","erroneous","or","maliciously","constructed","data",".","Never","unpickle","data","received","from","an","untrusted","or","unauthenticated","source",".","Parameters","--","--","--","--","--","fname",":","{","str",",","handle","}","A","string","filename","or","a","file","handle",".","Returns","--","--","--","-","Results","The","unpickled","results","instance","."]
code: def load(cls, fname):
      """
      Load a pickled results instance
  
      .. warning::
  
         Loading pickled models is not secure against erroneous or
         maliciously constructed data. Never unpickle data received from
         an untrusted or unauthenticated source.
  
      Parameters
      ----------
      fname : {str, handle}
          A string filename or a file handle.
  
      Returns
      -------
      Results
          The unpickled results instance.
      """
      from statsmodels.iolib.smpickle import load_pickle
  
      return load_pickle(fname)
  
file_path: statsmodels/statsmodels/base/wrapper.py
imports: import functools
  import inspect
  from textwrap import dedent
label_desc: Use image node_id 7 for calling the ResultsWrapper obj's underlying member method code with example usage: obj.load(cls, fname) and returns: load_pickle