Imitation Models and the Revolution in Open-Source LLM
Large language models (LLMs) from the LLaMA suite [2] were proposed, which sparked an upsurge in literature on open-source LLMs. These projects frequently aimed to create smaller, open-source LLMs with equivalent quality to proprietary models like ChatGPT and GPT-4 on a budget for research reasons. These models use an imitation method to enhance a foundational LLM using artificial dialogue data from a stronger LLM. These models appeared to function similarly to proprietary LLMs like ChatGPT despite being less expensive to train. The deep learning research community swiftly came to the conclusion that open-source LLMs will dominate in the future since it was simple and cost-effective to produce open-source versions of proprietary models.
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