You can still leverage knowledge from a foundation model in a smaller fine-tuned one.

So the model might have learned general OOP principles from Java but it then drops redundant parameters about specific conventions like AbstractFactoryBuilders when it specialises on a language like Python which has no notion of Interfaces.

Likewise real world knowledge might help distinguish between accounting and database transactions when writing a banking application but you don't necessarily need your coding assistant to have memorised all the world cup winners since 1966.

These models are unwieldy so I think it makes a lot of sense to try and find ones that are tuned efficiently.

The brown scum on the first two images could just be tannin from black tea. You can peel this/ the stained layers off the scoby. You can avoid it next time by not letting the tea "stew" i.e. removing the tea bag sooner (you might also need to use a water filter).

You can increase the yield with a bigger container. It needs to have a wide mouth to maximise the amount of surface exposed to air relative to the volume of liquid. I personally find my kombucha too acidic after a week so need to dilute it in a closed secondary fermentation (to fizz up) which doubles the yield.

It might just be that they dried up in the hot weather. If so they'll uncurl now it's rained.

You might also want to check for ants breeding black fly on the underside. They suck the moisture from the leaves causing them to curl over. You can usually just scrape them off with a wet finger.