Update README.md

README.md

@@ -1,3 +1,4 @@
+---
 title: Ministral WebGPU
 emoji: ⚡️
 colorFrom: red
@@ -9,43 +10,56 @@ short_description: Frontier multimodal AI, running entirely in your browser.
 app_build_command: npm run build
 app_file: dist/index.html
 models:
-  - mistralai/Ministral-3-3B-Instruct-2512-ONNX
-  - mistralai/Ministral-3-3B-Instruct-2512
+- mistralai/Ministral-3-3B-Instruct-2512-ONNX
+- mistralai/Ministral-3-3B-Instruct-2512
+---
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
+# AI Multimodal WebGPU Assistant
 
-AI Multimodal WebGPU Assistant
-Developer: Muhammad Abdullah Rasheed Research Assistant @ Cambridge | MSc Data Science & AI '25 | Google WTM Scholar
+**Developer:** Muhammad Abdullah Rasheed
+**Research Assistant @ Cambridge | MSc Data Science & AI '25 | Google WTM Scholar**
+
+## Overview
 
-Overview
 This project demonstrates cutting-edge browser-based AI by running a complete 3B parameter multimodal language model entirely client-side using WebGPU acceleration. No servers, no API calls, no data sent anywhere - complete privacy and instant inference.
 
-Key Features
-Privacy-First Architecture: The entire Ministral-3B model runs locally in your browser using WebGPU - your video feed never leaves your device
-Real-Time Multimodal AI: Live camera feed processing with visual question answering capabilities
-WebGPU Acceleration: Leveraging the latest browser GPU APIs for near-native performance
-Zero Backend Dependencies: No API keys, no server calls, no external services required
-Cross-Platform: Works seamlessly across modern browsers with WebGPU support
-Technical Stack
-Model: Ministral-3-3B-Instruct (quantized for browser deployment)
-Runtime: Transformers.js for in-browser inference
-Compute: WebGPU API for GPU acceleration
-Frontend: Modern JavaScript with WebAssembly integration
-Use Cases
-Visual question answering from live camera feed
-Real-time scene understanding and description
-Privacy-sensitive AI applications
-Edge computing demonstrations
-Educational tool for AI and browser technologies
-Why This Matters
+## Key Features
+
+- **Privacy-First Architecture**: The entire Ministral-3B model runs locally in your browser using WebGPU - your video feed never leaves your device
+- **Real-Time Multimodal AI**: Live camera feed processing with visual question answering capabilities
+- **WebGPU Acceleration**: Leveraging the latest browser GPU APIs for near-native performance
+- **Zero Backend Dependencies**: No API keys, no server calls, no external services required
+- **Cross-Platform**: Works seamlessly across modern browsers with WebGPU support
+
+## Technical Stack
+
+- **Model**: Ministral-3-3B-Instruct (quantized for browser deployment)
+- **Runtime**: Transformers.js for in-browser inference
+- **Compute**: WebGPU API for GPU acceleration
+- **Frontend**: Modern JavaScript with WebAssembly integration
+
+## Use Cases
+
+- Visual question answering from live camera feed
+- Real-time scene understanding and description
+- Privacy-sensitive AI applications
+- Edge computing demonstrations
+- Educational tool for AI and browser technologies
+
+## Why This Matters
+
 This project showcases the future of AI deployment - moving powerful language models from cloud servers to the edge, where they can provide instant, private, and accessible intelligence without compromising user privacy or requiring expensive infrastructure.
 
-Author
-Muhammad Abdullah Rasheed
-Research Assistant | AI & Machine Learning Researcher
+## Author
+
+**Muhammad Abdullah Rasheed**  
+Research Assistant | AI & Machine Learning Researcher  
+- 🎓 MSc Data Science & AI '25, Google WTM Scholar  
+- 🔬 Research areas: Computer Vision, NLP, Climate AI  
+- 💼 Experience: Gesture Recognition, Backend Development, ML Engineering  
+- 🔗 [LinkedIn](https://www.linkedin.com/in/muhammad-abdullahrasheed-/) | [GitHub](https://github.com/Abdullahrasheed45) | [HuggingFace](https://huggingface.co/Abdullahrasheed45)
+
+## License
 
-🎓 MSc Data Science & AI '25, Google WTM Scholar
-🔬 Research areas: Computer Vision, NLP, Climate AI
-💼 Experience: Gesture Recognition, Backend Development, ML Engineering
-🔗 LinkedIn | GitHub | HuggingFace
-License
 Apache-2.0