code: def _create_model(self, module):
      m = module.model()
  
      m.support_vectors = to_table(self.support_vectors_)
      m.coeffs = to_table(self.dual_coef_.T)
      m.biases = to_table(self.intercept_)
  
      if (
          self.svm_type is SVMtype.c_svc
          or self.svm_type is SVMtype.nu_svc
      ):
          m.first_class_response, m.second_class_response = 0, 1
      return m
  
imports: from abc import ABCMeta, abstractmethod
  from enum import Enum
  from numbers import Number, Real
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator
  from daal4py.sklearn._utils import sklearn_check_version
  from onedal import _backend
  from ..common._estimator_checks import _check_is_fitted
  from ..common._mixin import ClassifierMixin, RegressorMixin
  from ..common._policy import _get_policy
  from ..datatypes import from_table, to_table
  from ..utils import _check_array, _check_n_features, _check_X_y, _column_or_1d, _validate_targets
label_desc: Use image node_id 7 for calling the BaseSVM obj's underlying member method code with example usage: obj._create_model(module) and returns: m