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Optimizing Large Language Model Selection for Efficient GenAI Development

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Speakers: Royal Sequeira, Machine Learning Engineer, Georgian Aslesha Pokhrel, Machine Learning Engineer, Georgian Christopher Tee, Software Engineer, Georgian Abstract: When developing a Generative AI use case, developers face a variety of choices, particularly with the proliferation of foundational and open-source models. The decision process to choose the suitable large language model (LLM) for a given use case, however, may involve fine-tuning, crafting tailored prompts, cost considerations, and evaluations, which can become cumbersome without a modular design approach. In this workshop, we will explore various tools such as DSPy and frugalGPT to help pick the best LLM given the usecase. This will be a hands-on session focusing on the practical applications.

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