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      "@value" : " Evolver, model merging in a genetic algorithm\nImproves on current merging techniques (my beloved TIES 🫣 )\nTrain diverse models\nMerge regularly or take diff between two models\nUpdate some parameters\nKeep if good\nRepeat\n\nhttps://arxiv.org/abs/2406.12208\n@jingli9111 @banting_liu @576gsk https://twitter.com/LChoshen/status/1803410440535326786/photo/1\n\n Merging is aimed at taking many models and getting one that generalizes better, there are various methods for it, read more e.g. on TIES\nhttps://x.com/prateeky2806/status/1665759148380758022\n\n Genetic algorithms evolve models, in steps:\nCreate mutations (here new m = m_old + a(m_1-m_2)) m are models a some constant\n\nCrossover, take some of the mutation and apply it, for each parameter randomly keep m_old or update to m_new\n\nSurvive, keep only the best performing on val\n\n By sometimes merging and sometimes evolving (and dev sets) they improve over all current methods https://twitter.com/LChoshen/status/1803410445635653960/photo/1\n\n In some sense, this can be seen as a better search in the region between the merged models, which we know is not equally good but all better than the edges\nhttps://x.com/LChoshen/status/1729488495515713672 https://twitter.com/LChoshen/status/1803410447246250483/photo/1\n\n"
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