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Zdarma

Why You Should [Not] Fine-Tune on Synthetic Data

  Machine learning

Speaker: Roman Grebennikov Description Custom task-specific LLMs offer significant benefits in terms of privacy (they can be run locally), costs (eliminating per-request API fees), and quality (optimized for your specific business problem). Building such a model with existing tools is straightforward—if you have enough training data. However, in practice, you often don't.In this talk, we'll share the story of how we built a synthetic training data generation tool for the open-source search engine Nixiesearch. We'll use the open ESCI dataset and explore how much we can improve search releva...