Technically, you could do that, but we trained this one from the ground up!
That sounds like an enormously expensive exercise.
As someone who's done something similar (https://blog.lukesalamone.com/posts/creating-tiny-semantic-s...) the expensive part wasn't the training itself but the data curation and evaluation post-training. For this, getting a reasonable distribution of tool calls when the tool call can be anything isn't easy.
Once you have that, the model is small enough batch sizes are probably enormous and training can probably be done on a consumer-grade GPU in a week or less. Or even faster on a bigger GPU.
Training scales pretty badly, so smaller models like this are really not that bad in terms of cost.
You can train a model of this size on your laptop in a day.