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Why isn't someone providing a "meta model" that uses an LLM to choose between various fine tuned models depending on the question to get overall better results
by colordrops 2y ago
Why isn't someone providing a "meta model" that uses an LLM to choose between various fine tuned models depending on the question to get overall better results than gpt4?
- billmalarky 2y agoFounding 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/#conditional-edges 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!
- sheepscreek 2y agoVery loosely, isn’t this what is happening inside most LLMs that have a “multi-head” mechanism?
- bashfulpup 2y agoAlready a big thing. See the constellation architecture used here: https://arxiv.org/html/2403.13313v1 https://arxiv.org/html/2403.13313v1
- drphilwinder 2y agoCheck out https://unify.ai/chat https://unify.ai/chat if you're interested in a router optimised for cost/ttft/performance for commercial language models.
- anon373839 2y agoWorth mentioning that you don’t even need separate models to implement this. Dynamically loading LoRA adapters is much more efficient, and is the approach Apple took.