3 ms·
Sure, but note that a tiny LLM is many order of magnitudes larger than algorithms like this. It might well work better, but you're probably paying for very, ver
by emn13 6d ago
Sure, but note that a tiny LLM is many order of magnitudes larger than algorithms like this. It might well work better, but you're probably paying for very, very marginal improvements with a solution that's thousands of times larger and slower, unless you're you're being really creative and using a fairly non-LLM network of perceptrons or other ML technique. But it sounds like a fun challenge; if you or anybody feels like exploring that, I bet it'd get quite a few curious clicks here!
- docheinestages 6d agoIt really depends on the use case, which the author didn't hint to (sure, they say procedurally generating text, but exactly how and for what reason?). But whatever it is, I assume it needs to be accurate to some degree, and having a deterministic ruleset is just too subjective and superficial to cover all cases. It doesn't need to be a full-fledged LLM either. What I mean is that a probabilistic machine learning model trained on a sufficiently large dataset is probably a better choice here. Small language models are pretty efficient nowadays, even for on-device use cases with constrained resources.