Update README.md with new model card content

README.md

@@ -4,7 +4,7 @@ library_name: keras-hub
 ### Model Overview
 # Model Summary
 
-The Moonshine models are trained for the speech recognition task, capable of transcribing English speech audio into English text. Useful Sensors developed the models to support their business direction of developing real time speech transcription products based on low cost hardware. There are 2 models of different sizes and capabilities, summarized in the presets table.
+The Moonshine models are designed for English speech recognition, capable of transcribing spoken audio into accurate English text. Developed by Useful Sensors, these models align with the company’s focus on real-time transcription solutions built for low-cost, resource-efficient hardware. Moonshine is available in two variants, each offering a different balance of size and performance, outlined in the presets table below.
 
 Weights are released under the [MIT License](https://www.mit.edu/~amini/LICENSE.md) . Keras model code is released under the [Apache 2 License](https://github.com/keras-team/keras-hub/blob/master/LICENSE).
 
@@ -35,8 +35,8 @@ The following model checkpoints are provided by the Keras team. Full code exampl
 
 | Preset name                            | Parameters | Description                                                                                                  |
 |---------------------------------------|------------|--------------------------------------------------------------------------------------------------------------|
-|  moonshine_base_en  |     61.5M   |  Moonshine base model for English speech recognition.Developed by Useful Sensors for real-time transcription.|
-|  moonshine_tiny_en    |  27.1M      | Moonshine tiny model for English speech recognition. Developed by Useful Sensors for real-time transcription. |
+|  moonshine_base_en  |     61.5M   |  For real-time transcription, Moonshine Base is a portable, powerful English voice recognition model. It is perfect for applications where accuracy and speed are crucial since it provides excellent accuracy with extremely low latency.|
+|  moonshine_tiny_en    |  27.1M      | For real-time transcription, Moonshine Tiny is a compact and efficient English voice recognition model. It’s ideal for resource-constrained applications where low latency and reliable accuracy are essential. |
 
 ## Example Usage
 ```Python