zlacker

>>tosh+(OP)
Doesn’t really follow instructions too well, if you ask it to list 10 songs on or 5 things it’s give you way more. I’m not sure why some models do it well like Mistral instruct v1, ChatGPT 3.5/4 but here it extremely verbose and it outputs like a short circuited robot

>>m3kw9+GG
>> Doesn’t really follow instructions too well,

This is the biggest problem we're having swapping LLMs. While Langchain allows easy swap, and while we dont care as much about quality during integration testing, etc...the bigger problem is following directions. OpenAI does well at outputting a JSON if I ask for one. Unfortunately now our software has come to expect JSON output in such cases. Swap it to, say, llama2 and you dont get JSON even if asking for one. This makes swapping not just a quality decision but an integration challenge.

>>Turing+CO
In my experience, Llama 2 (70B) can semi-reliably provide JSON output when provided with clear instructions and various distinct but similarly structured examples. It goes from “semi-reliably” to “consistently” when fine-tuned.

The primary issue I’ve run into is exhausting the context window much sooner than I’d like. Fine-tuning tends to mostly fix this issue though.