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

575 points · 225 comments · firelex

  1. AgentMasterRace · · focus · HN ↗
    I compared it to Jev in my current use cases and it's very inaccurate. 70% vs 94% . for classification, it's unacceptable.
    1. tbeseda · · focus · HN ↗
      For _your_ classification it's unacceptable. The OP seems to have anticipated this and mentions you can fine tune it for your use case. Did you try that?

      I don't think the point is to displace Jev, but to show it's possible to build an MVP on open weights without years of work and millions of dollars.

      Why (presumably) an engineer would dismiss exploring a lightweight, custom alternative to locking into a fashionable PaaS, I'll never know.

      1. senko · · focus · HN ↗
        > The OP seems to have anticipated this and mentions you can fine tune it for your use case. Did you try that?

        You can already so that with classification models such as ModernBERT, at 0.4B.

        Jev's value is its zero shot performance without having to fine-tune.

        1. beepbooptheory · · focus · HN ↗
          I am sure I am missing something obvious here, but why is that valuable? Like, what kinds of projects are there where you need to classify stuff but are unable to make a bespoke model targeting the specific problem?
          1. jmalicki · · focus · HN ↗
            > unable to make a bespoke model targeting the specific problem?

            There is a fixed cost (and some maintenance) to e.g. fine tuning ModernBERT.

            Maybe once you include all of that it might be a half-day to a day of engineering time to set everything up in a maintainable fashion.

            For Jev, it takes all of 30 seconds of prompting. And it's not that much more expensive to deploy vs. a BERT model.

            1. benterix · · focus · HN ↗
              The biggest disadvantage of Jev is that it's a proprietary product and you need to send them your data. A bespoke solution makes much more sense in many scenarios.
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