Update README.md with new model card content

README.md

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 library_name: keras-hub
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-This is a [`ESM` model](https://keras.io/api/keras_hub/models/esm) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
-This model is related to a `MaskedPLM` task.
-
-Model config:
-* **name:** esm_backbone
-* **trainable:** True
-* **vocabulary_size:** 33
-* **num_layers:** 30
-* **num_heads:** 20
-* **hidden_dim:** 640
-* **intermediate_dim:** 2560
-* **dropout:** 0.0
-* **max_wavelength:** 10000
-* **use_bias:** True
-* **activation:** gelu
-* **layer_norm_eps:** 1e-05
-* **use_pre_layer_norm:** False
-* **position_embedding_type:** rotary
-* **max_sequence_length:** 1026
-* **pad_token_id:** 1
-
-This model card has been generated automatically and should be completed by the model author. See [Model Cards documentation](https://huggingface.co/docs/hub/model-cards) for more information.
+### Model Overview
+Evolutionary Scale Modeling (ESM) version 2 architecture.
+
+**Reference**
+
+- [Evolutionary-scale prediction of atomic level protein structure with a language model](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v2)
+
+ESM-2 is a state-of-the-art protein model trained on a masked language modelling objective. It is suitable for fine-tuning on a wide range of tasks that take protein sequences as input.
+
+## Links
+
+* [ESM-2 Quickstart Notebook] - coming soon
+* [ESM-2 API Documentation] - coming soon
+* [ESM-2 Beginner Guide] - coming soon
+* [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. Weights have been ported from: https://huggingface.co. Full code examples for each are available below.
+
+| Preset name                        | Parameters | Description                                                                                                                                                                                                                                                                                               |
+|------------------------------------|------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| esm2_t6_8M | 8M      | 6 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset. |
+| esm2_t12_35M | 35M      | 12 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset. |
+| esm2_t30_150M | 150M      | 30 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset. |
+| esm2_t33_650M | 650M     | 33 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset. |
+