Update README.md with new model card content

README.md

@@ -2,21 +2,35 @@
 library_name: keras-hub
 pipeline_tag: text-generation
 ---
-This is a [`PARSeq` model](https://keras.io/api/keras_hub/models/par_seq) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
-This model is related to a `CausalLM` task.
-
-Model config:
-* **name:** par_seq_backbone
-* **trainable:** True
-* **dtype:** {'module': 'keras', 'class_name': 'DTypePolicy', 'config': {'name': 'float32'}, 'registered_name': None}
-* **image_encoder:** {'module': 'keras_hub.src.models.vit.vit_backbone', 'class_name': 'ViTBackbone', 'config': {'name': 'encoder', 'trainable': True, 'dtype': {'module': 'keras', 'class_name': 'DTypePolicy', 'config': {'name': 'float32'}, 'registered_name': None}, 'image_shape': [32, 128, 3], 'patch_size': [4, 8], 'num_layers': 12, 'num_heads': 6, 'hidden_dim': 384, 'mlp_dim': 1536, 'dropout_rate': 0.0, 'attention_dropout': 0.0, 'layer_norm_epsilon': 1e-06, 'use_mha_bias': True, 'use_mlp_bias': True, 'use_class_token': False, 'use_patch_bias': True}, 'registered_name': 'keras_hub>ViTBackbone'}
-* **vocabulary_size:** 97
-* **max_label_length:** 25
-* **decoder_hidden_dim:** 384
-* **num_decoder_layers:** 1
-* **num_decoder_heads:** 12
-* **decoder_mlp_dim:** 1536
-* **dropout_rate:** 0.1
-* **attention_dropout:** 0.1
-
-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
+Permuted autoregressive sequence (PARSeq) model for Scene Text Recognition (STR)
+
+This model is designed for Scene Text Recognition (STR), which involves reading text from images. You can load and use the pre-trained PARSeq model with the following Python code snippet. The model takes an image as input and outputs the recognized text.
+
+## Links
+
+* [PARSeq Quickstart Notebook]()
+* [PARSeq API Documentation](https://keras.io/api/keras_hub/models/parseq/)
+* [PARSeq Model Card](https://www.kaggle.com/models/keras/parseq)
+* [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>=3
+```
+
+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                                                                                          |
+|----------------------------------------|------------|----------------------------------------------|
+| `parseq`              | 23.8M      | 23 million parameter base model.                                                  |
+