Matryoshka
Matryoshka Representation Learning (MRL) dafay tàggat ay embedding ngir leeral yi gëna am solo ñu boole leen ci dimension yi njëkk, loolu dina tax nga mëna dagg vecteur bu gudd ci bu gëna gàtt te doo ñàkk lu bari.
Résumé
Like nested Russian dolls, one embedding contains many usable smaller embeddings.
Plongeur bu xóot
Kusupati ak ñeneen ñi ñoo ko dugal ci atum 2022, Jàngum Representation Matryoshka dafay defar benn lëkkale bu prefix yi ci seen bopp nekk lëkkalekaay yu baax. Modèle bi dañu ko tàggat ak perte buñ boole muy gëna mëna liggéey ci dimension yu bari yuñ boole, ci misaal 8, 16, 32, ba 2048 dimension, ñoom ñépp bokk benn poid. Ndax coordonnée yu njëkk ya ñoo yor leeral yi gëna ñaaw, gëna wuute, mën nga dagg 64 wala 256 nimero yi njëkk ba noppi nga am resultaa yu am doole, ba noppi nga denc vecteur yu mat yi ci barab yi gëna jubal. Loolu dafay tax ñu mëna jëfandikoo: vecteur yu yomb, yu am dimension yu woyof ngir seetlu bu gaaw bu njëkk, ginaaw ga ñu delloo ko ci rang ak vecteur yu mat sëkk. OpenAI's xeetu bind-3 dafa siiwal MRL ci fësal ab parametru dimension buñ tabax ci pexe bii.
Gis-gis xarala
Kafe taggat bi mooy perte nested: ngir prefix bu nekk ci guddaay biñ tànn, model bi dafay xayma boppam ci classification wala perte contrastif ci jëfandikoo dimension yi jiitu rek, ba noppi perte yooyu dañu leen boole. Degrade yi dañuy puus reso bi ngir mu jël siñaal bi gëna am njariñ ci kanam. Ci tënk, dagg ba ci k dimension ak renormalise dafay joxe ab embedding bu baax, soxlawul retraining. Loolu wuute na ak PCA wala model yu wuute ci dayo bu nekk, te loolu dafay laaj xayma wala dencukaay bu gëna bari.
njeextalu pexe
Gaawaay ak yaatuwaay
Liggéeyukaay yi ci làkk yi mën nañu gëna gaaw te duñu yàq deggoo gi.
Dugg ak yegg
Dafay yaatal jëfandikoo gi ci làkk yi ak ci anam yi ñuy jokkoo.
dogal yu gëna leer
Ekip yi mën nañu gëna yàgg ci àtte ci jamono ji otomatisation di liggéey ci baamtu.
Ëlëgu Matryoshka
Matryoshka embeddings nekk na mënin buñ jagleel ci modelu embedding komersiyaal ak ubbeeku ndax dañuy wàññi vecteur-database dencukaay ak njëgu seetlu te kenn duko tàggataat. Xaarandil lëkkaloo bu gëna dëgër ak kantite (Matryoshka boole ci vecteur binaire wala int8) ngir kompresioŋ bu tar, pipeline yiy jël dimensionnalité ci laaj bu nekk, ak yokk xalaatu représentation nested ci multimodal ak embeddings nataal fu dencukaay bi gëna rëy.
Doxal ci àdduna dëgg
Denc ay vecteur yu gàtt yu am 256 dimension ci biir base de done vecteur ngir seetlu bu yomb te yaatu, ba noppi nga defaraat rang yi gëna mag ak vecteur yu mat
Jëfandikoo OpenAI's mbind-saggat-3 'dimensions' paramet ngir wàññi samp gi te doo tàggataat xeetu bees
Doxal seetlu semantik ci aparey ci telefon yu am memory bu néew
boole dagg Matryoshka ak kantite binar ngir mëna ànd ak ay miliyaar ciy vecteur ci biir RAM bu néew
Risk yi ak balustrade yi
Lépp lu jaarul yoon mën na dugg ci rapoor yi, jàppale ci liggéey bi, wala ci njariñu gëstu bi.
Sensibilite bu gaaw mën na jur njariñ yu wuute ci laajte yu noonu mel.
Done yu am solo mën nañu feeñ sudee seytu jëfandikoo gi néew doole.
Roadmap ngir samp gi
Mandargal formaa génne gi, melokaan bi, ak standard kalite yi laata ngay dugal ko.
Tontu yu am solo ak balluwaay yu wóor saa yu dëggu bi di am solo.
Fexeel am barabu xool nit ñi ngir am njariñ yu am solo.
Toppal anami gacce yi ak di faral di tàggataat ay laaj wala def-liggéey.
Weyal di banneexu
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Gis bi ci topp
Audio yuñ dugal ak jàngat ci representation
Laaj yi ñuy faral di laaj
What is Matryoshka Representation Embeddings?
Matryoshka Representation Learning (MRL) dafay tàggat ay embedding ngir leeral yi gëna am solo ñu boole leen ci dimension yi njëkk, loolu dina tax nga mëna dagg vecteur bu gudd ci bu gëna gàtt te doo ñàkk lu bari. Bu demee ni puppe russe yuñ defaree lënd, benn lëkkale amna lëkkalekaay yu ndaw yu bari yuñ mëna jëfandikoo.
Lan mooy màndarga gi gëna am solo ci Matryoshka?
MRL dafay jël leeral yi ci kanam, suko defee ñu dagg ko ci prefix bu gëna gàtt, ba leegi dafay joxe embedding bu dëgër, melni puppe yuñ defaree nest.
naka lañuy tàggatee xeetu Matryoshka ngir mëna def loolu?
MRL dafay gëna mëna ñàkk ci dimension yu bari yuñ boole ci benn yoon, suko defee prefix bu nekk jàng am njariñ.
Lan ngay def ci inference ngir am embedding bu gëna ndaw?
Dangay dagg coordonnée k yi nga defaraat; amul benn tàggat wala royukaay bu gëna mag.
Ban xeetu jënd ak jaay moo siiwal Matryoshka jaaraleko ci parametru 'dimension' yi?
OpenAI's xeetu bind-3 dafay may jëfandikukat yi ñu gàttal dugal ci ab parametru dimension buñ tabax ci kaw MRL.
Lan mooy njariñ li gëna am solo ci dugal Matryoshka?
Soo jëfandikoo vecteur yu gëna gàtt ngir seetlu bu njëkk bu yomb ak yu gëna gudd ngir rang bu bees, MRL dafay wàññi njëgu dencukaay bi ak xayma yi.