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Explore dynamic routing in Unify to optimize query performance based on user-defined latency, cost, and quality budgets. Learn how to implement thresholds for directing queries to the most suitable LLM provider, balancing performance and resource allocation. Gain insights into leveraging this feature to enhance AI model deployment efficiency and cost-effectiveness. Discover practical applications of dynamic routing in machine learning workflows, with a focus on large language models like Llama and Llama 2. Connect with the community on Discord for further discussions and access additional resources in the documentation for a deeper understanding of runtime routing concepts.
Syllabus
Unify: Demos - 03 Routing to Minimize Cost & Latency
Taught by
Unify