I see there is progress being made on smaller LLMs that have fewer parameters, but as I understand they are just trying to optimize how much information can be fit in a given parameter size. Is there work being done on LLMs that are trained on less information? For example say I want to chat with a PDF, I don’t care for my LLM to speak French, be able to write Python or know that Benjamin Franklin wrote a paper on flatuence (all things RWKV v5 World 1.5B knows).
“I want to chat with a PDF, I don’t care for my LLM to speak French, be able to write Python or know that Benjamin Franklin wrote a paper on flatuence (all things RWKV v5 World 1.5B knows).”
This is Prime RAG, bring snippets in, make the model use them. The more knowledge the model has, the better it gets for your usecase as well, as it knows more stuff.
Also, nice using rwkv v5, hows it work for you?