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    ‘Antidoom’ training aims to reduce small AI models’ ‘doom loops’

    A Liquid AI team member says the company uses final token preference optimization (FTPO) to tackle loops that small models with thinking capabilities can enter on complex tasks.

    CS
    KK
    2 Sources, 15d ago, first seen 15d ago

    TLDR

    A Liquid AI team member shares a tutorial on “antidoom” training, saying the company uses final token preference optimization (FTPO) to address “doom loops” in small models with thinking capabilities. They describe the tutorial as covering what doom loops are, how to reduce them with FTPO, and how to implement a custom DPOTrainer class in TRL.

    Combined views

    17

    2 Sources, first seen 15d ago

    Combined views

    17

    2 Sources, first seen 15d ago

    13 reposts
    13 reposts

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    2 Sources

    @CShorten30RT @helloiamleonie: models can get stuck in "doom loops" when • the model is small, • it has thinking capabilities, • and the task is compl…
    @kastnerkyleRT @helloiamleonie: models can get stuck in "doom loops" when • the model is small, • it has thinking capabilities, • and the task is compl…

    2 Sources

    @CShorten30RT @helloiamleonie: models can get stuck in "doom loops" when • the model is small, • it has thinking capabilities, • and the task is compl…
    @kastnerkyleRT @helloiamleonie: models can get stuck in "doom loops" when • the model is small, • it has thinking capabilities, • and the task is compl…