diff --git a/tests/test_models.py b/tests/test_models.py
index bb2a92ed..aa866ccd 100644
--- a/tests/test_models.py
+++ b/tests/test_models.py
@@ -56,7 +56,7 @@ FEAT_INTER_FILTERS = [
     'regnet', 'byobnet', 'byoanet', 'mlp_mixer', 'hiera', 'fastvit', 'hieradet_sam2', 'aimv2*',
     'tiny_vit', 'vovnet', 'tresnet', 'rexnet', 'resnetv2', 'repghost', 'repvit', 'pvt_v2', 'nextvit', 'nest',
     'mambaout', 'inception_next', 'inception_v4', 'hgnet', 'gcvit', 'focalnet', 'efficientformer_v2', 'edgenext',
-    'davit',
+    'davit', 'rdnet', 'convnext', 'pit'
 ]
 
 # transformer / hybrid models don't support full set of spatial / feature APIs and/or have spatial output.
diff --git a/timm/models/convnext.py b/timm/models/convnext.py
index 2f445118..e2eb48d3 100644
--- a/timm/models/convnext.py
+++ b/timm/models/convnext.py
@@ -486,8 +486,8 @@ class ConvNeXt(nn.Module):
     ):
         """ Prune layers not required for specified intermediates.
         """
-        take_indices, max_index = feature_take_indices(len(self.stages) + 1, indices)
-        self.stages = self.stages[:max_index]  # truncate blocks w/ stem as idx 0
+        take_indices, max_index = feature_take_indices(len(self.stages), indices)
+        self.stages = self.stages[:max_index + 1]  # truncate blocks w/ stem as idx 0
         if prune_norm:
             self.norm_pre = nn.Identity()
         if prune_head:
diff --git a/timm/models/pit.py b/timm/models/pit.py
index 109cfaf8..1d5386a9 100644
--- a/timm/models/pit.py
+++ b/timm/models/pit.py
@@ -313,7 +313,7 @@ class PoolingVisionTransformer(nn.Module):
         """ Prune layers not required for specified intermediates.
         """
         take_indices, max_index = feature_take_indices(len(self.transformers), indices)
-        self.stages = self.stages[:max_index + 1]  # truncate blocks w/ stem as idx 0
+        self.transformers = self.transformers[:max_index + 1]  # truncate blocks w/ stem as idx 0
         if prune_norm:
             self.norm = nn.Identity()
         if prune_head:
@@ -380,7 +380,7 @@ def _create_pit(variant, pretrained=False, **kwargs):
         variant,
         pretrained,
         pretrained_filter_fn=checkpoint_filter_fn,
-        feature_cfg=dict(feature_cls='hook', no_rewrite=True, out_indices=out_indices),
+        feature_cfg=dict(feature_cls='hook', out_indices=out_indices),
         **kwargs,
     )
     return model