Small custom GPT-2 models (30-124M parameters) can match larger LLMs on three sensor-classification tasks and run faster on edge computers.
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone, 2024
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TinyLLM: A Framework for Training and Deploying Language Models at the Edge Computers
Small custom GPT-2 models (30-124M parameters) can match larger LLMs on three sensor-classification tasks and run faster on edge computers.