Llama Legend Personalized Diabetes Plan
In the Edge Runners 3.2 Hackathon, we're creating a Personalized Diabetes Plan app using Meta's advanced Llama 3.2 models. Our approach focuses on three key objectives: Generate Synthetic Data: Leveraging Llama 3.2's capabilities, we create high-quality, diverse datasets to enhance data variety and improve model training. Optimize Models: We train smaller models such as TinyLlama and Phi-3 to maximize their performance on edge devices like smartphones, tablets, and IoT devices. Deploy on Edge Devices: Our cloud prototypes are designed for seamless integration on edge hardware, ensuring efficient local data processing without relying heavily on centralized cloud resources. This project showcases our innovative solution's potential to run sophisticated AI models directly on edge devices, transforming diabetes management into a highly personalized experience.
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"Even though the synthetic data generation approach needs more validation for healthcare applications its a great project"
Theodoros Ampas
Technical Mentor
"Not for edge runner devices and basic application"
Shebagi Mitra
Technical Mentor
For Innovators & Creators