diff --git a/timm/models/byobnet.py b/timm/models/byobnet.py
index f9b10755..e999dd7b 100644
--- a/timm/models/byobnet.py
+++ b/timm/models/byobnet.py
@@ -2355,7 +2355,7 @@ default_cfgs = generate_default_cfgs({
     'test_byobnet.r160_in1k': _cfgr(
         hf_hub_id='timm/',
         first_conv='stem.conv',
-        input_size=(3, 160, 160), crop_pct=0.875, pool_size=(5, 5),
+        input_size=(3, 160, 160), crop_pct=0.95, pool_size=(5, 5),
     ),
 })
 
diff --git a/timm/models/convnext.py b/timm/models/convnext.py
index 612f8acd..004d8e83 100644
--- a/timm/models/convnext.py
+++ b/timm/models/convnext.py
@@ -953,14 +953,17 @@ default_cfgs = generate_default_cfgs({
         input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=1.0, num_classes=1024),
 
     "test_convnext.r160_in1k": _cfg(
-        # hf_hub_id='timm/',
-        input_size=(3, 160, 160), pool_size=(5, 5), mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5)),
+        hf_hub_id='timm/',
+        mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
+        input_size=(3, 160, 160), pool_size=(5, 5), crop_pct=0.95),
     "test_convnext2.r160_in1k": _cfg(
-        # hf_hub_id='timm/',
-        input_size=(3, 160, 160), pool_size=(5, 5), mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5)),
+        hf_hub_id='timm/',
+        mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
+        input_size=(3, 160, 160), pool_size=(5, 5), crop_pct=0.95),
     "test_convnext3.r160_in1k": _cfg(
-        # hf_hub_id='timm/',
-        input_size=(3, 160, 160), pool_size=(5, 5), mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5)),
+        hf_hub_id='timm/',
+        mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
+        input_size=(3, 160, 160), pool_size=(5, 5), crop_pct=0.95),
 
 })
 
diff --git a/timm/models/efficientnet.py b/timm/models/efficientnet.py
index 57a77aaa..07bb250c 100644
--- a/timm/models/efficientnet.py
+++ b/timm/models/efficientnet.py
@@ -1804,19 +1804,18 @@ default_cfgs = generate_default_cfgs({
 
     "test_efficientnet.r160_in1k": _cfg(
         hf_hub_id='timm/',
-        input_size=(3, 160, 160), pool_size=(5, 5)),
+        input_size=(3, 160, 160), pool_size=(5, 5), crop_pct=0.95),
+    "test_efficientnet_ln.r160_in1k": _cfg(
+        hf_hub_id='timm/',
+        input_size=(3, 160, 160), pool_size=(5, 5), crop_pct=0.95),
     "test_efficientnet_gn.r160_in1k": _cfg(
         hf_hub_id='timm/',
         mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
-        input_size=(3, 160, 160), pool_size=(5, 5)),
-    "test_efficientnet_ln.r160_in1k": _cfg(
-        #hf_hub_id='timm/',
-        mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
-        input_size=(3, 160, 160), pool_size=(5, 5)),
+        input_size=(3, 160, 160), pool_size=(5, 5), crop_pct=0.95),
     "test_efficientnet_evos.r160_in1k": _cfg(
-        #hf_hub_id='timm/',
+        hf_hub_id='timm/',
         mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
-        input_size=(3, 160, 160), pool_size=(5, 5)),
+        input_size=(3, 160, 160), pool_size=(5, 5), crop_pct=0.95),
 })
 
 
diff --git a/timm/models/nfnet.py b/timm/models/nfnet.py
index 42aaee22..2aa27564 100644
--- a/timm/models/nfnet.py
+++ b/timm/models/nfnet.py
@@ -736,9 +736,9 @@ default_cfgs = generate_default_cfgs({
     'nf_ecaresnet101': _dcfg(url='', first_conv='stem.conv'),
 
     'test_nfnet.r160_in1k': _dcfg(
-        # hf_hub_id='timm/',
+        hf_hub_id='timm/',
         mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
-        crop_pct=0.875, input_size=(3, 160, 160), pool_size=(5, 5)),
+        crop_pct=0.95, input_size=(3, 160, 160), pool_size=(5, 5)),
 })
 
 
diff --git a/timm/models/resnet.py b/timm/models/resnet.py
index 4bda521d..432b1182 100644
--- a/timm/models/resnet.py
+++ b/timm/models/resnet.py
@@ -1304,8 +1304,8 @@ default_cfgs = generate_default_cfgs({
         first_conv='conv1.0'),
 
     'test_resnet.r160_in1k': _cfg(
-        #hf_hub_id='timm/',
-        mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
+        hf_hub_id='timm/',
+        mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), crop_pct=0.95,
         input_size=(3, 160, 160), pool_size=(5, 5), first_conv='conv1.0'),
 })
 
diff --git a/timm/models/vision_transformer.py b/timm/models/vision_transformer.py
index 2a574fe6..2c9c7f4a 100644
--- a/timm/models/vision_transformer.py
+++ b/timm/models/vision_transformer.py
@@ -2014,13 +2014,13 @@ default_cfgs = {
 
     'test_vit.r160_in1k': _cfg(
         hf_hub_id='timm/',
-        input_size=(3, 160, 160), crop_pct=0.875),
+        input_size=(3, 160, 160), crop_pct=0.95),
     'test_vit2.r160_in1k': _cfg(
-        #hf_hub_id='timm/',
-        input_size=(3, 160, 160), crop_pct=0.875),
+        hf_hub_id='timm/',
+        input_size=(3, 160, 160), crop_pct=0.95),
     'test_vit3.r160_in1k': _cfg(
         #hf_hub_id='timm/',
-        input_size=(3, 160, 160), crop_pct=0.875),
+        input_size=(3, 160, 160), crop_pct=0.95),
 }
 
 _quick_gelu_cfgs = [
@@ -3217,21 +3217,23 @@ def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> Visio
 def test_vit(pretrained: bool = False, **kwargs) -> VisionTransformer:
     """ ViT Test
     """
-    model_args = dict(patch_size=16, embed_dim=64, depth=6, num_heads=2, mlp_ratio=3)
+    model_args = dict(patch_size=16, embed_dim=64, depth=6, num_heads=2, mlp_ratio=3, dynamic_img_size=True)
     model = _create_vision_transformer('test_vit', pretrained=pretrained, **dict(model_args, **kwargs))
     return model
 
 
+@register_model
 def test_vit2(pretrained: bool = False, **kwargs) -> VisionTransformer:
     """ ViT Test
     """
     model_args = dict(
         patch_size=16, embed_dim=64, depth=8, num_heads=2, mlp_ratio=3,
-        class_token=False, reg_tokens=1, global_pool='avg', init_values=1e-5)
+        class_token=False, reg_tokens=1, global_pool='avg', init_values=1e-5, dynamic_img_size=True)
     model = _create_vision_transformer('test_vit2', pretrained=pretrained, **dict(model_args, **kwargs))
     return model
 
 
+@register_model
 def test_vit3(pretrained: bool = False, **kwargs) -> VisionTransformer:
     """ ViT Test
     """