Deploying GPT-like models on edge devices requires aggressive pruning, distillation, and quantization techniques.
While large language models are resource-hungry, edge-optimized finetuned variants like TinyGPT are opening new frontiers.
Bringing intelligent NLP to the edge ecosystem.
These smaller models can handle smart home automation, local voice assistants, and contextual offline predictions.
Companies are embracing these techniques to bring personalized intelligence to IoT and embedded systems.
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