Update README.md with new model card content

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: keras-hub
 ---
-### Model Overview
+## Model Overview
 BERT (Bidirectional Encoder Representations from Transformers) is a set of language models published by Google. They are intended for classification and embedding of text, not for text-generation. See the model card below for benchmarks, data sources, and intended use cases.
 
 Weights and Keras model code are released under the [Apache 2 License](https://github.com/keras-team/keras-hub/blob/master/LICENSE).
@@ -41,7 +41,7 @@ The following model checkpoints are provided by the Keras team. Full code exampl
 | `bert_large_en_uncased`  | 335.14M    | 24-layer BERT model where all input is lowercased. |
 | `bert_large_en`          | 333.58M    | 24-layer BERT model where case is maintained. |
 
-### Example Usage
+## Example Usage
 ```python
 import keras
 import keras_hub