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> If you want to change what the model can present, fine tuning is a hopeless way of doing it. If this is what I want, then what is the right way to do it?
by CMCDragonkai 3y ago
> If you want to change what the model can present, fine tuning is a hopeless way of doing it.
If this is what I want, then what is the right way to do it?
- BoorishBears 3y agoPut the information in the context window of the model. If you're answering questions on current events, hook it up to a news API and let it take in a user query, return a search to you, and give the result back to the LLM before it responds. Right now LLMs perform best for factual information if you treat them like flexible glue between the user and your data sources. Any knowledge you leverage from the LLM itself should "static" knowledge that can hold true across all user queries. For example, you can use the LLM's knowledge of marketing to produce marketing copy via chain of thought. Trends in marketing copy can change, but the actual act of making marketing copy takes a static set of knowledge. _ Don't use the LLM to surface competitors for the product, because one person will ask about 'Coke' and it'll say 'Pepsi', and another will name their founded in 2023 company and it'll hallucinate: especially if you're asking for structured output Instead let the LLM form some searches, take the results and let the LLM use chain of thought on what defines a competitor, and surface that result
- CMCDragonkai 3y agoOk but what about transfer learning the LLM, are there practical ways of building more static knowledge into the LLM? Long term memory and all that?
- BoorishBears 3y agoPutting knowledge in the context window enables the same thing For example, letting the LLM return a result to the user and return a list of entities it wants to save details on for later, then letting it query past entries allows long term memory for a class of entities. Over all it will be a very long time before approaches like that are beat by fine tuning, because as the models improve, this strategy gets stronger: the model gets better are crafting queries, you can provide more context in the context window. Meanwhile fine tuning in knowledge will get more difficult as MOE and other unforseen developments reset what works as far as directly tinkering with weights.
- visarga 3y agoFine-tune a different base model. There are plenty to pick from, just pick one that hast the kind of knowledge you want.
- icelancer 3y agoUsing a RAG is probably best here.