I might be biased by the products I'm building but it feels to me that function support is table stakes now? Are open source models are just missing the dataset to fine tune one?
Very few of the models supported on Groq/Together/Fireworks support function calling. And rarely the interesting ones (DeepSeek V3, large llamas, etc)
100%. we've found that llama-3.3-70b-versatile and qwen-qwq-32b perform exceptionally well with reliable function calling. we had recognized the need for this and our engineers partnered with glaive ai to create fine tunes of llama 3.0 specifically for better function calling performance until the llama 3.3 models came along and performed even better.
i'd actually love to hear your experience with llama scout and maverick for function calling. i'm going to dig into it with our resident function calling expert rick lamers this week.
Thank you for saying this out loud. I've been losing my mind wondering where the discussion on this was. LLMs without Tool Use/Function Calling is basically a non starter for anything I want to do.
When I was working with LLMs without function calling I made the scaffold put some information in the system prompt that tells it some JSON-ish syntax it can use to invoke function calls.
It places more of a "mental burden" on the model to output tool calls in your custom format, but it worked enough to be useful.
Very few of the models supported on Groq/Together/Fireworks support function calling. And rarely the interesting ones (DeepSeek V3, large llamas, etc)