Fastagger aims to democratise AI by providing software infrastructure that allows ML and AI models to run directly on edge devices. It aims to enable multimodal LLMs, i.e. models that capture different data types, and other ML models to operate beyond the constraints of traditional cloudbased and high-performance computing systems. Fastagger primarily targets users with lower-end smartphones who are often left behind due to unreliable or limited access to mobile internet. To achieve this goal, Fastagger is currently focused on adapting pre-trained models such as OLMo, DeepSeek, LLM360, Mistral, Mosaic or Llama through compression and fine-tuning. Compression is the process of reducing the number of parameters within a model, Sectores Inteligencia artificial Ubicación Nairobi, Kenia Etapa Inicie la sesión para ver los detalles Mercados Inicie la sesión para ver los detalles Modelo de cliente Inicie la sesión para ver los detalles Ingresos Inicie la sesión para ver los detalles Soportado por Make-IT in Africa > Africa4Future Contacto Inicie la sesión para ver los detalles Medios sociales