Kọ́ ẹ̀kọ́Ìròyìn Irinṣẹ́Iṣẹ́Iṣẹ́ wa

AI Gilosari Igba

Kí ni Apapọ Awọn amoye (MoE)?

Itumọ

Ohun faaji pẹlu specialized subnetworks ibi ti nikan ti a ti yan amoye nṣiṣẹ fun igbewọle.

Ṣawakiri ni kikun AI Gilosari Ṣawari gbogbo awọn itọsọna AI ọfẹ

IyasọtọIṣẹ-ṣiṣe nibiti awoṣe kan ti n fi igbewọle si ọkan tabi diẹ ẹ sii awọn ẹka ti a ti ni asọye.Sisun Window akiyesiApẹrẹ akiyesi nibiti ami ami kọọkan wa nikan si window iwọn ti o wa titi ti awọn ami ti o wa nitosi lati dinku iṣiro.Ifojusi MechanismApakan awoṣe ti o dojukọ aifọwọyi lori awọn ẹya ti o yẹ ti igbewọle kan nigbati o ba n ṣe iṣelọpọ kan.Pq-ti-eroAra ironu nibiti awoṣe AI kan ti bajẹ iṣoro kan sinu awọn igbesẹ agbedemeji.AGEKURUApẹrẹ awoṣe multimodal ti o kọ ẹkọ awọn aṣoju pinpin laarin ọrọ ati awọn aworan.Ṣe iṣiroAwọn orisun sisẹ ti o nilo lati ṣe ikẹkọ ati ṣiṣe awọn awoṣe, nigbagbogbo wọn ni awọn wakati FLOPS tabi GPU.

Kọ ẹkọ diẹ sii ninu awọn itọsọna ọfẹ wa

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

Wo tun

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