Router models trained on preference data dynamically select between strong and weak LLMs, cutting inference costs by more than 2x on benchmarks with no quality loss and showing transfer to new model pairs.
Starling-7b: Improving llm helpfulness & harmlessness with rlaif, November 2023
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RouteLLM: Learning to Route LLMs with Preference Data
Router models trained on preference data dynamically select between strong and weak LLMs, cutting inference costs by more than 2x on benchmarks with no quality loss and showing transfer to new model pairs.