Explore the process of fine-tuning and evaluating Language Learning Models (LLMs) using LangSmith for dataset management. The guide demonstrates the use of open-source LLMs and OpenAI’s new fine-tuning service, highlighting the rapid growth in the LLM ecosystem. It provides insights into when and how to fine-tune, the challenges of dataset collection and evaluation, and the potential of fine-tuning for specialized tasks. The article also presents a test case of fine-tuning LLaMA2-7b-chat and gpt-3.5-turbo for an extraction task.
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