diff --git a/src/nemos/basis.py b/src/nemos/basis.py
index 0b6eee9b..164936c7 100644
--- a/src/nemos/basis.py
+++ b/src/nemos/basis.py
@@ -1008,9 +1008,10 @@ def evaluate_on_grid(self, *n_samples: int) -> Tuple[Tuple[NDArray], NDArray]:
         Raises
         ------
         ValueError
-            - If the time point number is inconsistent between inputs or if the number of inputs doesn't match what
+            If the time point number is inconsistent between inputs or if the number of inputs doesn't match what
             the Basis object requires.
-            - If one of the n_samples is <= 0.
+        ValueError
+            If one of the n_samples is <= 0.
 
         Notes
         -----
diff --git a/src/nemos/glm.py b/src/nemos/glm.py
index d348028f..509d8beb 100644
--- a/src/nemos/glm.py
+++ b/src/nemos/glm.py
@@ -686,7 +686,7 @@ def fit(
             If ``init_params[i]`` cannot be converted to ``jnp.ndarray`` for all ``i``
 
         Examples
-        -------
+        --------
         >>> # example input
         >>> import numpy as np
         >>> X, y = np.random.normal(size=(10, 2)), np.random.poisson(size=10)
@@ -1516,12 +1516,17 @@ def fit(
         Raises
         ------
         ValueError
-            - If ``init_params`` is not of length two.
-            - If dimensionality of ``init_params`` are not correct.
-            - If ``X`` is not two-dimensional.
-            - If ``y`` is not two-dimensional.
-            - If the ``feature_mask`` is not of the right shape.
-            - If solver returns at least one NaN parameter, which means it found
+            If ``init_params`` is not of length two.
+        ValueError
+            If dimensionality of ``init_params`` are not correct.
+        ValueError
+            If ``X`` is not two-dimensional.
+        ValueError
+            If ``y`` is not two-dimensional.
+        ValueError
+            If the ``feature_mask`` is not of the right shape.
+        ValueError
+            If solver returns at least one NaN parameter, which means it found
             an invalid solution. Try tuning optimization hyperparameters.
         TypeError
             If ``init_params`` are not array-like
diff --git a/src/nemos/observation_models.py b/src/nemos/observation_models.py
index e4bc407c..bea7b3d6 100644
--- a/src/nemos/observation_models.py
+++ b/src/nemos/observation_models.py
@@ -868,9 +868,11 @@ def check_observation_model(observation_model):
         If the `observation_model` does not have one of the required attributes.
 
     TypeError
-        - If an attribute is not a callable function.
-        - If a function does not return a jax.numpy.ndarray.
-        - If 'inverse_link_function' is not differentiable.
+        If an attribute is not a callable function.
+    TypeError
+        If a function does not return a jax.numpy.ndarray.
+    TypeError
+        If 'inverse_link_function' is not differentiable.
 
     Examples
     --------
diff --git a/src/nemos/simulation.py b/src/nemos/simulation.py
index a2dc06d6..48af7008 100644
--- a/src/nemos/simulation.py
+++ b/src/nemos/simulation.py
@@ -60,8 +60,9 @@ def difference_of_gammas(
     Raises
     ------
     ValueError:
-        - If any of the Gamma parameters is lesser or equal to 0.
-        - If the upper_percentile is not in [0, 1).
+        If any of the Gamma parameters is lesser or equal to 0.
+    ValueError:
+        If the upper_percentile is not in [0, 1).
 
     References
     ----------
@@ -247,7 +248,6 @@ def simulate_recurrent(
     inverse_link_function :
         The inverse link function for the observation model.
 
-
     Returns
     -------
     simulated_activity :
@@ -294,7 +294,6 @@ def simulate_recurrent(
     >>> _ = plt.title("Simulated firing rates")
     >>> _ = plt.show()
     """
-
     if isinstance(feedforward_input, FeaturePytree):
         raise ValueError(
             "simulate_recurrent works only with arrays. "
diff --git a/src/nemos/utils.py b/src/nemos/utils.py
index 87ad0472..557b6c96 100644
--- a/src/nemos/utils.py
+++ b/src/nemos/utils.py
@@ -53,10 +53,11 @@ def validate_axis(tree: Any, axis: int):
     Raises
     ------
     ValueError
-        - If the specified axis is equal to or greater than the number of dimensions (`ndim`) of any array
+        If the specified axis is equal to or greater than the number of dimensions (`ndim`) of any array
         within the tree. This ensures that operations intended for a specific axis can be safely performed
         on every array in the tree.
-        - If the axis is negative or non-integer.
+    ValueError
+        If the axis is negative or non-integer.
     """
     if not isinstance(axis, int) or axis < 0:
         raise ValueError("`axis` must be a non negative integer.")