Serious question but if it hallucinates about almost everything, what's the use case for it?

▲ simonw 6 days ago | parent | next [-]

Fine-tuning for specific tasks. I'm hoping to see some good examples of that soon - the blog entry mentions things like structured text extraction, so maybe something like "turn this text about an event into an iCal document" might work?

	▲	turnsout 6 days ago \| parent \| next [-]
		Google helpfully made some docs on how to fine-tune this model [0]. I'm looking forward to giving it a try! `[0]: https://ai.google.dev/gemma/docs/core/huggingface_text_full_finetune`
	▲	CuriouslyC 6 days ago \| parent \| prev \| next [-]
		Fine tuning messes with instruction following and RL'd behavior. I think this is mostly going to be useful for high volume pipelines doing some sort of mundane extraction or transformation.
	▲	iib 6 days ago \| parent \| prev [-]
		This is exactly the fine-tuning I am hoping for, or I would do if I had the skills. I tried it with gemma3 270M and vanilla it fails spectacularly. Basically it would be the quickadd[1] event from google calendar, but calendar agnostic. [1] https://developers.google.com/workspace/calendar/api/v3/refe...

▲ striking 6 days ago | parent | prev | next [-]

It's intended for finetuning on your actual usecase, as the article shows.

▲ zamadatix 6 days ago | parent | prev | next [-]

I feel like the blog post, and GP comment, does a good job of explaining how it's built to be a small model easily fine tuned for narrow tasks, rather than used for general tasks out of the box. The latter is guaranteed to hallucinate heavily at this size, that doesn't mean every specific task it's fine tuned to would be. Some examples given were fine tuning it to efficiently and quickly route a query to the right place to actually be handled or tuning it to do sentiment analysis of content.

An easily fine tunable tiny model might actually be one of the better uses of local LLMs I've seen yet. Rather than try to be a small model that's great at everything it's a tiny model you can quickly tune to do one specific thing decently, extremely fast, and locally on pretty much anything.

▲ yifanl 6 days ago | parent | prev | next [-]

It's funny. Which is subjective, but if it fits for you, it's arguably more useful than Claude.

▲ luckydata 6 days ago | parent | prev | next [-]

Because that's not the job it was designed to do, and you would know by reading the article.

▲ mirekrusin 6 days ago | parent | prev | next [-]

The same as having a goldfish. You can train it to do a trick I guess.

▲ deadbabe 6 days ago | parent | prev | next [-]

Games where you need NPCs to talk random jiberrish.

▲ iLoveOncall 6 days ago | parent | prev | next [-]

Nothing, just like pretty much all models you can run on consumer hardware.

	▲	cyanydeez 6 days ago \| parent [-]
		This message brought to you by OpenAI: we're useless, but atleast theres a pay gate indicating quality!

▲ numpad0 6 days ago | parent | prev | next [-]

robotic parrots?

▲ rotexo 6 days ago | parent | prev [-]

An army of troll bots to shift the Overton Window?

	▲	ants_everywhere 6 days ago \| parent [-]
		oh no now we'll never hear the end of how LLMs are just statistical word generators