Update finetune detail, rerun model doc gen.

Author: rwightman

docs/models/.templates/code_snippets.md

@@ -56,7 +56,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('{{ model_name }}', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('{{ model_name }}', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/adversarial-inception-v3.md

@@ -64,7 +64,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('adv_inception_v3', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('adv_inception_v3', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/advprop.md

@@ -62,7 +62,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('tf_efficientnet_b0_ap', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('tf_efficientnet_b0_ap', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/big-transfer.md

@@ -60,7 +60,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('resnetv2_101x1_bitm', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('resnetv2_101x1_bitm', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/csp-darknet.md

@@ -62,7 +62,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('cspdarknet53', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('cspdarknet53', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/csp-resnet.md

@@ -60,7 +60,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('cspresnet50', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('cspresnet50', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/csp-resnext.md

@@ -60,7 +60,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('cspresnext50', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('cspresnext50', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/densenet.md

@@ -62,7 +62,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('densenet121', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('densenet121', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/dla.md

@@ -62,7 +62,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('dla102', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('dla102', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.

docs/models/dpn.md

@@ -62,7 +62,7 @@ To extract image features with this model, follow the [timm feature extraction e
 ## How do I finetune this model?
 You can finetune any of the pre-trained models just by changing the classifier (the last layer).
 ```python
-model = timm.create_model('dpn107', pretrained=True).reset_classifier(NUM_FINETUNE_CLASSES)
+model = timm.create_model('dpn107', pretrained=True, num_classes=NUM_FINETUNE_CLASSES)
 ```
 To finetune on your own dataset, you have to write a training loop or adapt [timm's training
 script](https://github.com/rwightman/pytorch-image-models/blob/master/train.py) to use your dataset.