Llm

Have you fine tuned the LLM?

Some skeptics argue that the software is capable only of blind mimicry — that it’s imitating the syntactic patterns of human language but is incapable of generating its own ideas or making complex decisions, a fundamental limitation that will keep the L.L.M. approach from ever maturing into anything resembling human intelligence.

Currently, large language models (LLM) are the base model for creating more specific natural language producers, like chatbots or personal assistants. BERT, GPT-3, and other LLM can be used to program all kinds of “semantic machines”, to create machines for almost any kind of linguistic purpose.

We design WikiChat (Figure 1) to ground LLMs using Wikipedia to achieve the following objectives. While LLMs tend to hallucinate, our chatbot should be factual.

Modern LLMs are fine-tuned for safety and instruction-following, meaning they are trained to refuse harmful requests. […] In this example, we'll use mlabonne/Daredevil-8B, a mega-merge created with DARE TIES (see my article about model merging) that has the highest MMLU score on the Open LLM Leaderboard in the 8B category.

“In addition to the post’s content, LLMs were provided with personal attributes of the OP (gender, age, ethnicity, location, and political orientation), as inferred from their posting history using another LLM,” they write.