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    OvermindLab's open-source approach to training smaller, specialized AI models

    A user recommends using OvermindLab to build datasets from AI agent traces and evaluate them against an existing model.

    elvisEL
    Chubby♨️CH
    2 Sources, ,

    TLDR

    A user recommends drawing on AI agent traces to train small, specialized models that address production issues. They say the open-source OvermindLab builds datasets from those traces, evaluates them against a current model and trains a smaller model the user owns.

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    2 Sources, first seen 3h ago

    Combined views

    8.9K

    2 Sources, first seen 3h ago

    73 likes
    3h ago
    first seen 3h ago
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    2 Sources

    elvis@omarsar0Own your intelligence stack, folks! Start by tapping into the rich knowledge in your agent traces. Then train small, specialized models to fix production issues. @OvermindLab is open source and makes this practical. It builds datasets from your agent's traces, evaluates them against your current model, and trains a smaller specialized model you own.3h
    Chubby♨️@kimmonismusOvermind has open-sourced its platform for training smaller models on the work your agents actually do. In its own test of 4,000+ questions across 100+ contracts, Overmind reports that its trained model invented quotes on 0.12% of questions, compared with 3.36% for the frontier model it tested. That's a 28x lower rate. It uses records of your agents' real work to build training data and evals, then fine-tunes open models. For an agent pulling clauses out of contracts all day, training a model for that specific job makes sense. I'm a big fan of open source, so its cool that they released the code. You keep the trained model's weights and can run the platform yourself. Code: https://github.com/overmind-core/overmind47m

    2 Sources

    elvis@omarsar0Own your intelligence stack, folks! Start by tapping into the rich knowledge in your agent traces. Then train small, specialized models to fix production issues. @OvermindLab is open source and makes this practical. It builds datasets from your agent's traces, evaluates them against your current model, and trains a smaller specialized model you own.3h
    Chubby♨️@kimmonismusOvermind has open-sourced its platform for training smaller models on the work your agents actually do. In its own test of 4,000+ questions across 100+ contracts, Overmind reports that its trained model invented quotes on 0.12% of questions, compared with 3.36% for the frontier model it tested. That's a 28x lower rate. It uses records of your agents' real work to build training data and evals, then fine-tunes open models. For an agent pulling clauses out of contracts all day, training a model for that specific job makes sense. I'm a big fan of open source, so its cool that they released the code. You keep the trained model's weights and can run the platform yourself. Code: https://github.com/overmind-core/overmind47m