Founding AI Engineer at OpenPipe here, using a fine tuned "router LLM" to route between various specialized (inc fine tuned but not necessarily) applied models depending on the input is becoming a common pattern in more modern "graph like" LLM applications.
You can see how that "routing function" could include a call to a "Router LLM." And yes, fine tuning is a great method to better improve the routing intelligence of said Router LLM.
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Founding AI Engineer at OpenPipe here, using a fine tuned "router LLM" to route between various specialized (inc fine tuned but not necessarily) applied models depending on the input is becoming a common pattern in more modern "graph like" LLM applications.
See LangGraph's "conditional edges" concept here: https://langchain-ai.github.io/langgraph/concepts/low_level/...
You can see how that "routing function" could include a call to a "Router LLM." And yes, fine tuning is a great method to better improve the routing intelligence of said Router LLM.
Great question btw!