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Jeff – Jev-compatible 0.8B decision models, trained at home, ~30 ms

firelex · 569 points · 222 comments · yesterday · Open original

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hadlockyesterday

If you're looking for a more impressive doom example, I put together laya-duum which uses open source micropython implementation of doom (duum) and freeware freedoom1.wad. It uses the standard jev api and will play through the first two levels to completion: https://github.com/Hadlock/laya-duum

vektormemoryyesterday

Can someone remove the extra LLM and just have an embedder do the classifier work? It's turning into pimp my llm...

trebligdivadyesterday

What proportion of commercial LLM use is classification? I'm just wondering what happens to business AI spending/data centre usage when they realise they don't need full LLMs.

AgentMasterRaceyesterday

I compared it to Jev in my current use cases and it's very inaccurate. 70% vs 94% . for classification, it's unacceptable.

olwmcyesterday

Sorry, do we have actual clear implementation details for Jev? I keep seeing these "recreations" or "Do Jev at home" but do we have access to their architecture? I haven't even used the product, I just find it strange.