alot of really small SLMs seem to be too small to even function properly.
however, there may be some unconventional uses for some of them.
one usecase keyword generation. heres what gemma-3-270m-it-qat-Q4_0 gave me
prompt: keywords similar to "construction"
Construction activities
* Construction design
* Construction equipment
* Construction management
* Construction materials
* Construction methodology
* Construction organization
* Construction planning
* Construction process
* Construction project
* Construction project details
* Construction project management
* Construction project management activities
* Construction project management assessment
* Construction project management checklist
* Construction project management document
* Construction project management evaluation
* Construction project management framework
* Construction project management methodology
* Construction project management plan
* Construction project management project
* Construction project management report
* Construction project management review
* Construction project management schedule
* Construction project management software
* Construction project management strategy
* Construction project management system
* Construction project management tool
* Construction project planning
* Construction project scope
* Construction schedule
* Construction strategy
* Construction work
```
90 TPS (but got stuck in a repeating loop)
i think theres alot of other uses. but they arent really LLM answer that people usually reach for an LLM.
What is the point of that?
Wrap it in a harness. Dump antipatterns. Keep the rest. Call it a ratchet. Loop that. Fail fast. Refine. See what sticks. Design a better harness. Augment that harness. If nothing good comes out, that's data and that is good.
I aged a month just reading this
Technologic. Technologic.
I am trying to fully understand this. Can you please elaborate further? Are you thinking about a heuristic based harness?
Not sure about keyword generation exactly as OP intends to apply this, but short simple code that needs to be validated on output seems like the better application. Models are tiny and fast, so mmap and run in parallel and race to what passes validation first. Each agent gets a git branch. Losers generate the anti patterns. Human or cheap tokens integrates the results from corpus back into harness. Next generation.
Thanks! Will explore this further.
There's some really close prior art here https://arxiv.org/abs/2404.00725
Cool paper. This makes me want to try to experiment with this. I have a 8GB VRAM card and 32GB DDR4.
So not ideal, currently I just pay for inference. Trying to get a model to punch above its weight would be kinda interesting to experiment with.
Using it to tag content can make it easier to search later, bookmark management for example
So what's the advantage of a generated list over "construction"?
Mostly the ratio of effort to convenience
I wouldn't bother thinking up tags for every article I bookmark
However it is nice if a local model on the device can generate tags automatically
But they seem like iterative synonyms. Hardly unique enough to useful tags for either lumping or splitting.
Oh I misunderstood, I read construction as manually making tags
Yes this particular list wouldn't be that helpful. A different prompt or some post processing would be needed. I'm not familiar with this model either
anything you want it to be.
be creative !
I can't think of single useful function. You might as well have generated nonsense syllables and invited us to attach them to words to create meaning.
That sounds like easy to remember password generation
Person. Woman. Man Camera. TV. How hard is that? Correct horse battery staple.