Update README.md with new model card content

README.md

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 library_name: keras-hub
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-### Model Overview
+## Model Overview
 The VGG model is a type of convolutional neural network (CNN) architecture designed for image recognition and classification tasks. Developed by the Visual Geometry Group at the University of Oxford, it was introduced in the paper titled "Very Deep Convolutional Networks for Large-Scale Image Recognition" by Karen Simonyan and Andrew Zisserman in 2014. This model is supported in both KerasCV and KerasHub. KerasCV will no longer be actively developed, so please try to use KerasHub.
 
 
@@ -31,7 +31,7 @@ The following model checkpoints are provided by the Keras team. Weights have bee
 | vgg_16_imagenet  | 14.71M     | 16-layer VGG model pre-trained on the ImageNet 1k dataset at a 224x224 resolution. |
 | vgg_19_imagenet  | 20.02M     | 19-layer VGG model pre-trained on the ImageNet 1k dataset at a 224x224 resolution. |
 
-### Example Usage
+## Example Usage
 ```python
 input_data = np.ones(shape=(2, 224, 224, 3))