Update README.md with new model card content

README.md

@@ -27,6 +27,35 @@ To load preset architectures and weights, use the `from_preset` constructor.
 Disclaimer: Pre-trained models are provided on an "as is" basis, without
 warranties or conditions of any kind.
 
+## Links
+
+* [ALBERT Quickstart Notebook](https://www.kaggle.com/code/laxmareddypatlolla/albert-quickstart-notebook)
+* [ALBERT  API Documentation](https://keras.io/keras_hub/api/models/albert/)
+* [ALBERT  Model Card](https://huggingface.co/docs/transformers/en/model_doc/albert)
+* [KerasHub Beginner Guide](https://keras.io/guides/keras_hub/getting_started/)
+* [KerasHub Model Publishing Guide](https://keras.io/guides/keras_hub/upload/)
+
+## Installation
+
+Keras and KerasHub can be installed with:
+
+```
+pip install -U -q keras-hub
+pip install -U -q keras
+```
+
+Jax, TensorFlow, and Torch come preinstalled in Kaggle Notebooks. For instructions on installing them in another environment see the [Keras Getting Started](https://keras.io/getting_started/) page.
+
+## Presets
+
+The following model checkpoints are provided by the Keras team. Full code examples for each are available below.
+| Preset name    | Parameters | Description                                      |
+|----------------|------------|--------------------------------------------------|
+| albert_base_en_uncased |   11.68M  | 12-layer ALBERT model where all input is lowercased. Trained on English Wikipedia + BooksCorpus.|
+| albert_large_en_uncased| 17.68M  | 24-layer ALBERT model where all input is lowercased. Trained on English Wikipedia + BooksCorpus. |
+| albert_extra_large_en_uncased |   58.72M  | 24-layer ALBERT model where all input is lowercased. Trained on English Wikipedia + BooksCorpus.   |
+| albert_extra_extra_large_en_uncased|   222.60M    |  12-layer ALBERT model where all input is lowercased. Trained on English Wikipedia + BooksCorpus.  |
+
 
 __Arguments__