I work on Gemma and Gemini models I want to echo Daniel's point here. Small finetuned models have their place even with larger general purpose models.

For example last year with Daniel/Unsloth's help we released a tiny specialized model that can get equivalent to Gemini level purpose specifically for FC. For folks that need efficient limited purpose models small models like this can fit a specific need.

https://blog.google/innovation-and-ai/technology/developers-...

Especially on device. https://developers.googleblog.com/on-device-function-calling...

It's the same with chips, we have general purpose CPUs but we still have specialized silicon for tasks that are smaller, more power efficient, cheaper, and because they're single purpose it simplifies and derisks certain designs.

And I have to add, if you want to learn about finetuning models efficiently the Unsloth guides are at the top of my list. They're practical, have all the technical details, and most importantly Daniel and the others are working around the clock to keep it up to date in what is an incredibly fast moving space of models and hardware. I am continually astounded by their work.

Function calling and also finetuning with FC is a big use-case across any companies - we constantly see large orgs have internal APIs with some schema, and JSON guided output is good, but finetuning with FC is just much more powerful since the model actually starts to understand how to utilize the tools more effectively!

Nice work with Gemma and Gemini as usual! :) Excited for more cool models this year!