Update intro card

README.md

@@ -20,29 +20,30 @@ pinned: false
 </div>
 
 ---
----
-
 ## [TI EdgeAI Model Hub](https://huggingface.co/TexasInstruments-EdgeAI)
 
-[![Models](https://img.shields.io/badge/models-50%2B-brightgreen)](https://huggingface.co/TexasInstruments-EdgeAI) [![Hardware](https://img.shields.io/badge/hardware-TI%20MPU-brightgreen)](https://huggingface.co/TexasInstruments-EdgeAI) [![License](https://img.shields.io/badge/license-Open%20Source-brightgreen)](https://huggingface.co/TexasInstruments-EdgeAI)
+[![Models](https://img.shields.io/badge/models-50%2B-brightgreen)](https://huggingface.co/TexasInstruments-EdgeAI) [![Hardware](https://img.shields.io/badge/hardware-TI%20MPUs-brightgreen)](https://huggingface.co/TexasInstruments-EdgeAI) [![License](https://img.shields.io/badge/license-Open%20Source-brightgreen)](https://huggingface.co/TexasInstruments-EdgeAI)
 
-**Bring Your Own Edge AI Models and deploy on with Texas Instruments MPUs with C7x NPU acceleration**
+**Bring Your Own Models and deploy on Texas Instruments Micro Processors with C7 NPU acceleration**
 
-edgeai-modelhub is a collection of example pre-trained, **hardware-optimized** AI models for TI edge devices — with easy scripts and config files for compilation, benchmark and deployment.
+<details open>
+edgeai-modelhub is a collection of example pre-trained AI models for TI edge devices — with easy scripts and config files for compilation, benchmark and deployment.
 
-- Hardware-optimized for TI MPU processors
+- Optimized for TI MPU processors
 - Benchmarked on real TI hardware
-- Portable across all various TI MPU devices
+- Portable across various TI MPU devices
 - Automated scripts for model compilation, benchmark & deployment
 
 **Use cases:** Automotive · Aerospace & Defense · Industrial · Surveillance · Robotics · Edge IoT
 
 **Multiple model families and large collection of models** spanning image classification (ResNet, ViT, ConvNeXt, DINO/DINOv2, MobileNetV3) and object detection (YOLO11/26/v8/X, RT-DETRv2, RTMDet, RF-DETR, DETR & more)
 
-**Validated on multiple devices** with C7 NPU accelerators - including AM62A, TDA4AEN/AM67A, TDA4VM, TDA4VE/TDA4VL/AM68A, and TDA4VH/AM69A device families.
+**Validated on multiple SOCs** with C7 NPU accelerators - including AM62A, TDA4AEN/AM67A, TDA4VM, TDA4VE/TDA4VL/AM68A, and TDA4VH/AM69A device families.
 
-## [Navigate to TI EdgeAI Model Hub →](https://huggingface.co/TexasInstruments-EdgeAI)
+### [Navigate to TI EdgeAI Model Hub →](https://huggingface.co/TexasInstruments-EdgeAI)
 Browse the full model catalog, docs & deployment guides
 
+</details>
+
 ---
----
+