diff --git a/timm/models/inception_resnet_v2.py b/timm/models/inception_resnet_v2.py
index 138470f7..f4efaf52 100644
--- a/timm/models/inception_resnet_v2.py
+++ b/timm/models/inception_resnet_v2.py
@@ -314,23 +314,19 @@ default_cfgs = generate_default_cfgs({
     # ported from http://download.tensorflow.org/models/inception_resnet_v2_2016_08_30.tar.gz
     'inception_resnet_v2.tf_in1k': {
         'hf_hub_id': 'timm/',
-        'url': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/inception_resnet_v2-940b1cd6.pth',
         'num_classes': 1000, 'input_size': (3, 299, 299), 'pool_size': (8, 8),
         'crop_pct': 0.8975, 'interpolation': 'bicubic',
         'mean': IMAGENET_INCEPTION_MEAN, 'std': IMAGENET_INCEPTION_STD,
         'first_conv': 'conv2d_1a.conv', 'classifier': 'classif',
-        'label_offset': 1,  # 1001 classes in pretrained weights
     },
     # As per https://arxiv.org/abs/1705.07204 and
     # ported from http://download.tensorflow.org/models/ens_adv_inception_resnet_v2_2017_08_18.tar.gz
     'inception_resnet_v2.tf_ens_adv_in1k': {
         'hf_hub_id': 'timm/',
-        'url': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ens_adv_inception_resnet_v2-2592a550.pth',
         'num_classes': 1000, 'input_size': (3, 299, 299), 'pool_size': (8, 8),
         'crop_pct': 0.8975, 'interpolation': 'bicubic',
         'mean': IMAGENET_INCEPTION_MEAN, 'std': IMAGENET_INCEPTION_STD,
         'first_conv': 'conv2d_1a.conv', 'classifier': 'classif',
-        'label_offset': 1,  # 1001 classes in pretrained weights
     }
 })
 
diff --git a/timm/models/inception_v3.py b/timm/models/inception_v3.py
index 98497081..1c2a407e 100644
--- a/timm/models/inception_v3.py
+++ b/timm/models/inception_v3.py
@@ -428,21 +428,14 @@ default_cfgs = generate_default_cfgs({
         hf_hub_id='timm/',
         url='https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth'),
     # my port of Tensorflow SLIM weights (http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz)
-    'inception_v3.tf_in1k': _cfg(
-        hf_hub_id='timm/',
-        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_inception_v3-e0069de4.pth',
-        num_classes=1000, label_offset=1),
+    'inception_v3.tf_in1k': _cfg(hf_hub_id='timm/'),
     # my port of Tensorflow adversarially trained Inception V3 from
     # http://download.tensorflow.org/models/adv_inception_v3_2017_08_18.tar.gz
-    'inception_v3.tf_adv_in1k': _cfg(
-        hf_hub_id='timm/',
-        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/adv_inception_v3-9e27bd63.pth',
-        num_classes=1000, label_offset=1),
+    'inception_v3.tf_adv_in1k': _cfg(hf_hub_id='timm/'),
     # from gluon pretrained models, best performing in terms of accuracy/loss metrics
     # https://gluon-cv.mxnet.io/model_zoo/classification.html
     'inception_v3.gluon_in1k': _cfg(
         hf_hub_id='timm/',
-        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/gluon_inception_v3-9f746940.pth',
         mean=IMAGENET_DEFAULT_MEAN,  # also works well with inception defaults
         std=IMAGENET_DEFAULT_STD,  # also works well with inception defaults
     )
diff --git a/timm/models/inception_v4.py b/timm/models/inception_v4.py
index 91c435d9..a43290a3 100644
--- a/timm/models/inception_v4.py
+++ b/timm/models/inception_v4.py
@@ -312,12 +312,10 @@ def _create_inception_v4(variant, pretrained=False, **kwargs) -> InceptionV4:
 default_cfgs = generate_default_cfgs({
     'inception_v4.tf_in1k': {
         'hf_hub_id': 'timm/',
-        'url': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-cadene/inceptionv4-8e4777a0.pth',
         'num_classes': 1000, 'input_size': (3, 299, 299), 'pool_size': (8, 8),
         'crop_pct': 0.875, 'interpolation': 'bicubic',
         'mean': IMAGENET_INCEPTION_MEAN, 'std': IMAGENET_INCEPTION_STD,
         'first_conv': 'features.0.conv', 'classifier': 'last_linear',
-        'label_offset': 1,  # 1001 classes in pretrained weights
     }
 })
 
diff --git a/timm/models/nasnet.py b/timm/models/nasnet.py
index edf355f8..954ee176 100644
--- a/timm/models/nasnet.py
+++ b/timm/models/nasnet.py
@@ -588,7 +588,6 @@ default_cfgs = generate_default_cfgs({
         'num_classes': 1000,
         'first_conv': 'conv0.conv',
         'classifier': 'last_linear',
-        'label_offset': 1,  # 1001 classes in pretrained weights
     },
 })
 
diff --git a/timm/models/pnasnet.py b/timm/models/pnasnet.py
index 23785007..bee18604 100644
--- a/timm/models/pnasnet.py
+++ b/timm/models/pnasnet.py
@@ -355,7 +355,6 @@ def _create_pnasnet(variant, pretrained=False, **kwargs):
 default_cfgs = generate_default_cfgs({
     'pnasnet5large.tf_in1k': {
         'hf_hub_id': 'timm/',
-        'url': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-cadene/pnasnet5large-bf079911.pth',
         'input_size': (3, 331, 331),
         'pool_size': (11, 11),
         'crop_pct': 0.911,
@@ -365,7 +364,6 @@ default_cfgs = generate_default_cfgs({
         'num_classes': 1000,
         'first_conv': 'conv_0.conv',
         'classifier': 'last_linear',
-        'label_offset': 1,  # 1001 classes in pretrained weights
     },
 })