Dhammaan ereyada

Transformers

Qaab-dhismeed shabakad neerfeed ah oo isticmaala attention si loo sameeyo xiriirinta dhammaan qaybaha isku-xigxiga (sequence) mar keliya.

Barashada Qoto dheer2 daqiiqo akhris

Qeexid

Qaab-dhismeedka Transformer, oo lagu soo bandhigay warqadda "Attention Is All You Need" (2017), wuxuu beddelay lakabyada recurrent isagoo isticmaalaya self-attention si loo qaabeeyo isku-xigxigga (sequence modeling).

Self-attention wuxuu u ogolaadaa token kasta oo ku jira isku-xigxig inuu miisaamo muhiimadda token kale kasta marka la dhisayo matalaadiisa — taasoo suurtogelinaysa xiriirro fog-fog (long-range dependencies) iyadoon la mari doonin caqabadaha habaynta isku-xigxiga.

Si fudud

Marka aad akhriyayso qodob, uma socotid ereyada tartiib ah oo bidix ilaa midig oo keliya. Waxaad si joogto ah dib ugu eegtaa kana fiirsataa horaanta si aad u xaliso magacyada beddelka (pronouns) iyo macnaha guud. Transformers-ku wuxuu si rasmi ah u qaabeeyaa 'fiirsashadaas hareeraha' iyadoo la isticmaalayo dhibcaha attention ee u dhexeeya lammaanaha erayada oo dhan.

Halka aad ka aragto

  • Qoysaska GPT, Claude, iyo Llama waa moodallo luqad oo ku salaysan Transformer.
  • Google Translate iyo nidaamyada MT-ga casriga ah waxay isticmaalaan Transformers.
  • Vision Transformers (ViT) waxay fikradda isku mid ah ku dabaqaan sawirrada.
  • Whisper iyo moodallada kale ee codka waxay isticmaalaan Transformer encoders/decoders.

Sida ay u shaqeyso

  1. 1.Token-ee wax soo galka

    Qoraalka waxaa loo kala qaybiyaa tokens, waxaana loo beddelaa vector-yo embedding ah.

  2. 2.Lakabyada self-attention

    Lakab kastaa wuxuu xisaabiyaa miisaanka attention-ka — inta uu token kastaa u fiirsan lahaa kuwa kale — kadibna wuxuu cusboonaysiiyaa matalaadyada.

  3. 3.Xarumaha feed-forward

    Shabakadaha neerfaha ee position-wise ayaa si dheeraad ah u beddela matalaadka token kasta.

  4. 4.Isku dubarid iyo saadaalin

    Lakabyo badan ayaa isku shubaya; lakabka ugu dambeeya wuxuu soo saaraa logits-ka token-ka xiga, calaamadda fasalka, ama madaxa howsha.

Maxay muhiim u tahay

  • Transformers waa aasaaska ku dhawaad dhammaan moodallada luqadda iyo multimodal-ka casriga ah ee heerka sare ah maanta.
  • Fahamka attention wuxuu cadeeyaa sababta context windows, ballaarinta (scaling), iyo qarashka xisaabinta ay u dhaqmaan sida ay u dhaqmaan.

Inta badan la khaldo

  • Transformers waxay si taxadar leh u xasuustaan qoraalka tababarka si dhab ah.

    Waxay bartaan matalaad la qaybiyay (distributed representations); xusuusnaanta si dhab ah way suurtogal tahay laakiin maaha farsamada koowaad ee guud-guudka (generalization).

  • Attention waa isku mid la raadinta (search).

    Attention waa qaab miisaamid oo far-dheeraad ah (differentiable) oo gudaha shabakadda neerfaha ku jira — ku dhawaad raadinta ruuxdeeda laakiin xisaab ahaan waa kala duwan tahay.