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GUIDE teknik
Gating ak routing dañuy may reso neuronal bi mu aktive wàll yi mu soxla ci input bu nekk, du def model bi yépp saa yu nekk.
Déglul tegtal biiIA-nettali · ~2 min
Loolu dafay tàqale dayo model bi ak njëgu ordinatër bi, loolu mooy tax model yu rëy yi di gaaw te yomb ci dox.
Calcul conditionnel mooy reso bi dafay jël dogal ci done yi ci ban sous-module lay jëfandikoo. Reseau 'gating' wala 'router' bu ndaw buñu jàng dafay xool bépp dugal (dafay faral di nekk token bu nekk) ba noppi defar ay poñ ngir tànn 'expert' yi mu koy yónnee. Ci biir Mixture-of-Experts (MoE) layer, ay fukki-fukki wala téemeeri sous-reseau expert am nañu ci, waaye routeur bi dafay tànn benn wala ñaar yi gëna kawe ci token bu nekk, moo tax expert yu bari duñu def dara ci bépp dugal buñ jox. Resultaa bi mooy benn model bu am limu parametre yu bari waaye limu aktif bu ndaw, loolu mooy jox dooley representation bu model bu mag ci njëgu runtime bu benn bu gëna ndaw. Noonu la model yu melni Transformer Switch, GLaM, ak model lakk yu mag yu bari di yegg ba ci ay trillion ci paramet ci anam wu yomb.
Transformatëru kommutatër bi dafay yóbbu token bu nekk ci benn eksper, muy yokk ba ëpp benn trillioŋ ciy parametre ci noonu muy tëye xayma bu token bu nekk.
Frontier model yu yaatu yu jëfandikoo njaxasu-ci-Expert layers suko defee benn wàll ci poid yi kese lañuy aktive ci token bu nekk.
Classificatëru nataal yiy teela genn, yuy taxaw ci layer bu xóotul ngir am nataal yu yomb, ba noppi di daw lu gëna xóot ngir nataal yu dëgër yi kese.
Modèle yu bari làkk yu routeurs yi di jàng yónnee ay token ci làkk yu wuute ci ay kàngam yu wuute.
Sparse gating mooy leegi lu am solo ci modelu frontiere yi, te tendaas bi mingi jëm ci kàngam yu gëna am pepp, routeurs yu gëna am xel, ak routing ci diisaay yu bari. Xaarandil pexe yu gëna baax ngir tàggat yaram bu dëgër, wàññi xaalis biy dugg ci jokkoo sudee eksper yi dañu tasaaroo ci accelerator yu bari, ak jàngat 'specialisation ekspert' ngir xam li eksper bu nekk di jàng. Calcul conditionnel itam mingi tasaaroo ginaaw MoE ci reso yu teela genn ak model dynamique-depth yuy gëna jëfandikoo calcul ci inputs yu gëna tar.
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Gating ak routing dañuy may reso neuronal bi mu aktive wàll yi mu soxla ci input bu nekk, du def model bi yépp saa yu nekk. Loolu dafay tàqale dayo model bi ak njëgu ordinatër bi, loolu mooy tax model yu rëy yi di gaaw te yomb ci dox.
The guide defines data-dependent selection of submodules as conditional computation.
The guide says a learned router selects experts based on its input.
Sparse routing can activate only part of the total parameter set per input.
The guide explains that most experts can remain idle for a particular token.
The guide notes routers can favor a few experts, leaving others underused.
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Ci bi mu melGis bi ci topp
LLM Njàngat ci Yoon ak Equilibrage de Charge
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