Uruvange rwinzobere (MoE) ni iki? Ibisobanuro | AI Understanding

Ibisobanuro

Ubwubatsi hamwe na subnetworks yihariye aho impuguke zatoranijwe zikora gusa kwinjiza.

Amagambo afitanye isano

Igikorwa aho icyitegererezo gitanga ibitekerezo kumurongo umwe cyangwa byinshi byateganijwe mbere.

Kunyerera Idirishya

Uburyo bwo kwitondera aho buri kimenyetso cyitabira gusa idirishya rinini ryerekana idirishya ryerekana ibimenyetso kugirango ugabanye compte.

Uburyo bwo Kwitondera

Icyitegererezo cyibanze cyibanda kubice byinjiza mugihe utanga umusaruro.

Urunigi-rw'ibitekerezo

Uburyo bwo gutekereza aho moderi ya AI ibora ikibazo murwego rwo hagati.

Moderi yuburyo bwububiko yiga gusangira hagati yinyandiko n'amashusho.

Ibikoresho byo gutunganya bisabwa guhugura no gukora moderi, akenshi bipimwa mumasaha ya FLOPS cyangwa GPU.

Wige byinshi mubuyobozi bwacu

Expert Parallelism for MoE Serving Mixture-of-Agents Aggregation Mixture of Depths Mixture of LoRA Experts

Reba kandi

Memory (Agent Memory)Model Card Machine Learning (ML)Model Drift Loss Function Model Quantization LoRA (Low-Rank Adaptation)Multimodal Model

Reba Amagambo yuzuye ya AI Shakisha ibyerekezo byose bya AI