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Hyper-Specific LLMs for Niche Applications
This chapter delves into the rise of large language models tailored for specific niches, such as Obsidian with 3 billion parameters, and the potential of deploying such models on edge devices like Linux boxes with limited RAM. It emphasizes the significance of language models with billions of parameters in generating human-readable, reasoning-driven responses to queries within specialized domains, exemplified by their contrast with earlier neural networks in tasks like image identification and metadata assignment.