Spaces:
Configuration error
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| title: Ministral WebGPU | |
| emoji: ⚡️ | |
| colorFrom: red | |
| colorTo: yellow | |
| sdk: static | |
| pinned: false | |
| license: apache-2.0 | |
| 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 | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| # AI Multimodal WebGPU Assistant | |
| **Developer:** Muhammad Abdullah Rasheed | |
| **Research Assistant @ Cambridge | MSc Data Science & AI '25 | Google WTM Scholar** | |
| ## 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 | |
| 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 | |
| - 🎓 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 | |
| Apache-2.0 |