1-Bit ak ñatti xeetu BitNet
BitNet mooy __AIU_PROTECTED_5_ lignéeru gëstu biy wane ni mën nañu tàggat modeli làkk yu mag ci diisaay bu yam ci 1 bit, wala ñetti valeur ci ternaire.
Résumé
This slashes memory and energy use dramatically while keeping surprisingly strong accuracy.
Plongeur bu xóot
Modèle yiñ gëna xam dañuy denc poid bu nekk ci nimero 16-bit. BitNet dafay wecci loolu ak ay misaali bit yu woyof lool. BitNet b1.58 bi am doole bi dafay jëfandikoo poid ternaire, bu nekk ci -1, 0, wala +1, loolu mooy liggéey ci lu tollu ci 1.58 bits ci poid bu nekk (log base 2 of 3). Li gëna am solo mooy ñu tàggat model bi ci noonu rek ak ay tënk, duñu ko xayma ci ganaw, suko defee mu jàng dëgër ci njubte gu gàtt gi. Ndax poid yi dañuy nekk -1, 0, wala +1, bariwaay yu seer yi ci math matrix dañuy daanu ci yokk ak dindi. Lépp soo ko boolee mu gëna néew bandwidth memory, konsommasioŋ energie, ak latency, ak valeur 0 bi itam may sparsity, lépp boole ci méngoo ak model yu mat sëkk ci dayo yuñ mëna méngale ci benchmark yu bari.
Gis-gis xarala
BitNet dafay jëfandikoo ab couche BitLinear buy xayma poid yi ci ternaire ak aktivasioŋ ci njubte bu woyof ci diiru paas bi ci kanam, ci noonu muy denc ab kopi 'lëndëm' bu gëna njubte ci poid yi ngir yeesali gradient jaaraleko ci estimatër bu jub. Ndax poids bu nekk mooy -1, 0, wala +1, produit dot yi ëpp doole ci transformateur yi dañuy nekk yokk ak dindi ludul yokk-point flottant, loolu mooy ubbi energie ak gaawaay ci hardware bi war.
njeextalu pexe
Njëgg ak budget
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw.
dogal yu gëna leer
Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal.
Xool kalite
Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi.
Ëlëgu xeetu BitNet 1-Bit ak Ternaire
BitNet dafay wane ëlëg gu model yu mëna daw ci telefon, ordinatër portable, ak aparey yu amul GPU datacenter. Bottleneck bi gëna mag mooy hardware bi: tay chips yi dañu leen tabax ngir math floating point, kon accelerator yuñ jagleel operation ternaire yuy yokk kese mën nañu yokk njariñ yi. Xaarandil yeneen architecture yu 1-bit, xeetu BitNet yu gëna mag, ak boole ci assistant yi ci aparey yi, fu dundu batëri ak nëbbëtu am solo, lu mëna soppi koom-koomu IA inference.
Doxal ci àdduna dëgg
BitNet b1.58 2B4T bu AIU dafay dox bu baax ci kaw CPU, loolu mooy tax LLM mëna jël dogal te amul GPU buñ jagleel.
Jàppalekat yi am ci aparey bi mëna ànd ak model bu mëna dem ci mémoire bu néew bi ci telefon bi ndax poids bu ~1.58-bit.
Wàññi energie inference ak njëgu karbon ngir sarwis API yu bari volume ci wecci poñ yuy flote ak yokk.
Deployment Edge (IoT, hardware buñ samp) fu poid ternaire yi di def ñu mëna dégg làkku dëkk bi ci biir budget yu néew.
Risk yi ak balustrade yi
Optimize benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi.
Njëg li ñuy fay ci infrastructure yi ak ci toppatoo dañuy faral di suufeel.
Bu sistem yi di gëna xawa jafee xam, jafe-jafe yi am ci wàllu kaaraange ak seetlu mën nañu gëna bari.
Roadmap ngir samp gi
Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo.
Benchmark ci biir sargal ak done yu dëggu.
Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi.
Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale.
Weyal di banneexu
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Gis bi ci topp
Modelu làkku filigran
Laaj yi ñuy faral di laaj
What is 1-Bit and Ternary BitNet Models?
BitNet mooy __AIU_PROTECTED_5_ lignéeru gëstu biy wane ni mën nañu tàggat modeli làkk yu mag ci diisaay bu yam ci 1 bit, wala ñetti valeur ci ternaire. Loolu dafay wàññi bu baax jëfandikoo mémoire ak energie ci noonu lañuy wéy di am njubte bu yéeme.
Lan moo waral ñu wax ni BitNet b1.58 dafay jëfandikoo lu tollu ci 1.58 bit ci poid bu nekk?
Poids ternaire yi dañuy jël benn ci ñatti valeur yi, te ngir wane ñatti etaa yi dañuy laaj base log 2 ci 3, lu tollu ci 1.58 bit.
Lan moo tax liggéeyu matrix BitNet gëna xéewale ci model yiñ miin?
Ak poid yu yam ci -1, 0, ak +1, yokk ci poid dafay wàññi yokk, dindi, wala baña bàyyi xel ci benn valeur, moytu yokk poñ flottant bu seer.
Ci diiru tàggat, naka la BitNet di yeesal poid yi doonte jéego kantite bi mënul wuute?
BitNet dafay denc ab kopi master bu gëna dëggu ci diisaay yi ba noppi di jëfandikoo estimatër bu jub ngir jaar ci gradient yi ci kantite bi, loolu mooy tax backpropagation bi jaar yoon.
Ban beneen njariñ la may valeur 0 (ternaire, du pure binaire)?
Etat 0 dafay tax yenn lëkkaloo yi ñu mëna fay, dugal sparsity buñ mëna jëfandikoo ngir gëna am njariñ.
Lan mooy jafe-jafe bi gëna mag ci hardware ngir xam njariñu efficacité bu mat sëkk ci BitNet?
Tay accelerator yi dañu leen sos ci lu wër floating-point multiplication, kon hardware buñ jagleel liggéey yu lalu ci yokk ternaire lañu soxla ngir mëna dindi gaawaayu BitNet ak njariñu energie.