diff --git a/botorch/models/fully_bayesian.py b/botorch/models/fully_bayesian.py
index 3a8282c250..da205046b7 100644
--- a/botorch/models/fully_bayesian.py
+++ b/botorch/models/fully_bayesian.py
@@ -644,8 +644,7 @@ def __init__(
         train_Yvar: Tensor | None = None,
         outcome_transform: OutcomeTransform | None = None,
         input_transform: InputTransform | None = None,
-        use_input_warping: bool = False,
-        indices_to_warp: list[int] = None,
+        pyro_model_kwargs: dict[str, Any] | None = None,
     ) -> None:
         r"""Initialize the fully Bayesian single-task GP model.
 
@@ -661,9 +660,8 @@ def __init__(
                 instantiation of the model.
             input_transform: An input transform that is applied in the model's
                 forward pass.
-            use_input_warping: A boolean indicating whether to use input warping.
-            indices_to_warp: An optional list of indices to warp. The default
-                is to warp all inputs.
+            pyro_model_kwargs: A dictionary of keyword arguments to pass to the
+                pyro model.
         """
         if not (
             train_X.ndim == train_Y.ndim == 2
@@ -703,10 +701,7 @@ def __init__(
         self.mean_module = None
         self.covar_module = None
         self.likelihood = None
-        self.pyro_model = self._pyro_model_class(
-            use_input_warping=use_input_warping,
-            indices_to_warp=indices_to_warp,
-        )
+        self.pyro_model = self._pyro_model_class(**pyro_model_kwargs)
         self.pyro_model.set_inputs(
             train_X=transformed_X, train_Y=train_Y, train_Yvar=train_Yvar
         )