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README.md

@@ -15,7 +15,7 @@ pipeline_tag: feature-extraction
 
 # AI Kit Gallery - Optimized ONNX Vision Models
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/huggingface/JanadaSroor/vision-models/blob/main/AI_Models_Demo.ipynb)
+[![View on Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20View%20Demo-Hugging%20Face-orange)](https://huggingface.co/JanadaSroor/vision-models/blob/main/AI_Models_Demo.ipynb)
 [![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Models-blue)](https://huggingface.co/JanadaSroor/vision-models)
 
 This repository contains optimized ONNX models designed for the [AI Kit Gallery](https://github.com/JanadaSroor/AIkit) Android app. These models enable high-performance, offline AI-powered image search and categorization directly on mobile devices.
@@ -45,8 +45,10 @@ This repository contains optimized ONNX models designed for the [AI Kit Gallery]
 ## 🚀 Quick Start
 
 ### 1. Try the Interactive Demo
-Test the models immediately using our Google Colab notebook:
-[**Run AI Models Demo in Colab**](https://colab.research.google.com/huggingface/JanadaSroor/vision-models/blob/main/AI_Models_Demo.ipynb)
+You can view or download the demo notebook from Hugging Face:
+[**View AI Models Demo**](https://huggingface.co/JanadaSroor/vision-models/blob/main/AI_Models_Demo.ipynb)
+
+*To run it in Colab: Download the `.ipynb` file and upload it to [Google Colab](https://colab.research.google.com/).*
 
 ### 2. Download Models
 ```bash