code: def RunNIST_Model(model):
      dset = ReadNistData(model)
      func, npar, dimx = Models[model]
      rss = (
          func(dset["cert_values"], x=dset["x"], y=dset["y"]) ** 2
      ).sum()
      tiny_rss = 1.0e-16
      print(rss, dset["sum_squares"], tiny_rss)
  
      if dset["sum_squares"] < tiny_rss:
          assert rss < tiny_rss
      else:
          assert_allclose(rss, dset["sum_squares"])
  
      out1 = NIST_Dataset(
          model, start="start1", plot=False, verbose=False
      )
      out2 = NIST_Dataset(
          model, start="start2", plot=False, verbose=False
      )
      assert out1 or out2
  
imports: import math
  from optparse import OptionParser
  from numpy.testing import assert_allclose
  from lmfit import Parameters, minimize
  from .NISTModels import Models, ReadNistData
label_desc: Use image node_id 6 for calling a global function with example usage: RunNIST_Model(model) without return types