Ask HN: How can I tell which LLM's have been trained on what?
I'm really no expert and attempting to come up to speed. But...
It strikes me that LLM's are a subtle combination of knowing the language and knowing some facts. If one were making a chatbot for helping (say) people understand their tax returns then you'd want a 'base' LLM that understood language and then add domain specific knowledge via RAG. So "yes" to knowing that Thursday comes after Wednesday; "no" to knowing how high Everest is; and questions regarding income tax have to reference the RAG. Is this correct?
So are there stock "thin" models for doing this? Is it better to train your own?
It strikes me that LLM's are a subtle combination of knowing the language and knowing some facts. If one were making a chatbot for helping (say) people understand their tax returns then you'd want a 'base' LLM that understood language and then add domain specific knowledge via RAG. So "yes" to knowing that Thursday comes after Wednesday; "no" to knowing how high Everest is; and questions regarding income tax have to reference the RAG. Is this correct?
So are there stock "thin" models for doing this? Is it better to train your own?