code: def remove_value_transforms(
      model: Model,
      vars: Optional[Sequence[ModelVariable]] = None,
  ) -> Model:
      """Remove the value variables transforms in the model
  
      Parameters
      ----------
      model : Model
      vars : Model variables, optional
          Model variables for which to remove transforms. Defaults to all transformed variables
  
      Returns
      -------
      new_model : Model
          Model with the removed transformed value variables
  
      Examples
      --------
      Extract untransformed space Hessian after finding transformed space MAP
  
      .. code-block:: python
  
          import pymc as pm
          from pymc.model.transform.conditioning import remove_value_transforms
  
          with pm.Model() as transformed_m:
              p = pm.Uniform("p", 0, 1)
              w = pm.Binomial("w", n=9, p=p, observed=6)
              mean_q = pm.find_MAP()
  
          with remove_value_transforms(transformed_m) as untransformed_m:
              new_p = untransformed_m["p"]
              std_q = ((1 / pm.find_hessian(mean_q, vars=[new_p])) ** 0.5)[0]
              print(f"  Mean, Standard deviation\\np {mean_q['p']:.2}, {std_q[0]:.2}")
  
          #   Mean, Standard deviation
          # p 0.67, 0.16
  
      """
      if vars is None:
          vars = model.free_RVs
      return change_value_transforms(model, {var: None for var in vars})
  
file_path: pymc/pymc/model/transform/conditioning.py
imports: import warnings
  from typing import Any, Mapping, Optional, Sequence, Union
  from pytensor.graph import ancestors
  from pytensor.tensor import TensorVariable
  from pymc import Model
  from pymc.logprob.transforms import Transform
  from pymc.logprob.utils import rvs_in_graph
  from pymc.model.fgraph import ModelDeterministic, ModelFreeRV, extract_dims, fgraph_from_model, model_deterministic, model_free_rv, model_from_fgraph, model_named, model_observed_rv
  from pymc.model.transform.basic import ModelVariable, parse_vars, prune_vars_detached_from_observed
  from pymc.pytensorf import replace_vars_in_graphs, toposort_replace
  from pymc.util import get_transformed_name, get_untransformed_name
label_desc: Use image node_id 4 for calling a global function with example usage: remove_value_transforms(model, vars) and returns: change_value_transforms