Update README.md with new model card content

README.md

@@ -9,18 +9,19 @@ Weights are released under the [MIT License](https://opensource.org/license/mit)
 
 ## Links
 
-* [Segmentation Quickstart Notebook](https://www.kaggle.com/code/divyasss/deeplabv3plus-quickstart)
-* [SegFormer API Documentation](https://keras.io/api/keras_cv/models/tasks/segformer_b0)
+* [Segmentation Quickstart Notebook](coming soon)
+* [SegFormer API Documentation](coming soon)
 * [SegFormer Model Card](https://huggingface.co/docs/transformers/en/model_doc/segformer)
-
+* [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 KerasCV can be installed with:
+Keras and KerasHub can be installed with:
 
 ```
-pip install -U -q keras-cv
-pip install -U -q keras>=3
+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.
@@ -38,22 +39,6 @@ The following model checkpoints are provided by the Keras team. Full code exampl
 | segformer_b4          | 61.37M     | SegFormer model with MiTB4 backbone.              |
 | segformer_b5          | 81.97M     | SegFormer model with MiTB5 backbone.              |
 
-## Example code
-
-```Python
-import keras_cv
-
-images = np.ones(shape=(1, 224, 224, 3))
-labels = np.zeros(shape=(1, 224, 224, 1))
-
-
-model = keras_cv.models.SegFormer.from_preset(
-            "segformer_b0", num_classes=2
-        )
-# Evaluate model
-model(images)
-```
-
 ## Example Usage
 ```python
 import keras_cv