- Imodeli yolimi ibikezela amathokheni ngokusekelwe kumongo, futhi ama-LLM alinganisa lo mbono ngezigidigidi zamapharamitha kanye nokwakheka kwe-Transformer.
- Ukuzinaka kuvumela ama-LLM ukuthi acabangele yonke inqubekela phambili ngesikhathi esisodwa, abambe ukuncika okude futhi enze kube lula ukuqeqeshwa okukhulu, okuhambisanayo.
- Izinhlelo ze-LLM ezifana ne-GPT, i-BERT, noma i-Llama ziqhuba izinhlelo zokusebenza zangempela: abasizi abangokoqobo, ukuhumusha, ukukhiqiza ikhodi, kanye nokwenza ngokuzenzakalela kwebhizinisi.
- Amandla ayo ahambisana nezingozi: imibono engekho, ukucwasa, izindleko eziphezulu zokubala, kanye nezinselele zokuziphatha nezokulawula ezidinga ukwamukelwa ngokwethembeka.
I-Los amamodeli olimi Sebeyinhliziyo yobuhlakani bokwenziwa besimanje: basemuva abasizi be-virtual nama-chatbotsUkuhumusha ngomshini namathuluzi abhala ikhodi noma umbhalo odwetshiwe cishe njengomuntu. Nakuba kungase kubonakale njengomlingo, empeleni kuhlanganisa izibalo, amanethiwekhi ezinzwa, kanye nenani elikhulu ledatha ukubikezela ukuthi yiliphi igama, ibinzana, noma ngisho nesithombe esinengqondo kakhulu esilandelayo.
Eminyakeni yamuva nje, okulandelayo kuye kwavela kakhulu: Amamodeli Olimi Olukhulu noma i-LLMLezi yizinguqulo ezinkulu kakhulu futhi ezinamandla kakhulu zamamodeli olimi ajwayelekile. Lezi zinhlelo azikhiqizi nje umbhalo ocacile, kodwa futhi zifingqa amadokhumenti, ziphendula imibuzo eyinkimbinkimbi, zihumushe phakathi kwezilimi, futhi zicabange ngisho nangokwezinga elithile. Ake sibheke kabanzi ukuthi ziyini, zisebenza kanjani ngaphakathi, yiziphi izinhlobo ezikhona, yiziphi izindlela zangempela ezisebenzisa ngazo ezinkampanini, kanye nezingozi kanye nemikhawulo okufanele ikhunjulwe.
Iyini ngempela imodeli yolimi?
Un imodeli yolimi Empeleni, uhlelo lwezibalo noma lwezibalo olunikeza amathuba okulandelana kwamathokheniIthokheni ingaba igama eliphelele, igama elingaphansi, noma ngisho nohlamvu olulodwa. Umgomo wemodeli ukulinganisa ukuthi yiliphi ithokheni okungenzeka livele ngokulandelayo ngokulandelana okunikeziwe.
Uma sicabanga ngomusho onesikhala, imodeli ibala yiziphi iziqephu ezilandelanayo ezingaba khona ezifanelana kahle kakhulu kanye nomongo. Isibonelo, uma kunikezwa umusho othi "Uma ngizwa imvula ophahleni lwami, ngi _______ ekhishini lami," uhlelo lulinganisa ezinye izindlela njengokuthi "isobho lokupheka," "ukushisa igedlela," noma "ukuthatha isihlwathi," lunikeza ngayinye ithuba elihlukile. Uhlelo lokusebenza lungakhetha inketho enethuba eliphezulu kakhulu noma isampula phakathi kwabalingani abaningana abangaphezu komkhawulo othile ukuze lunikeze ukuhlukahluka.
Le ndlela efanayo bikezela ithokheni elilandelayo Ngokwemvelo kudlulela emisebenzini eyinkimbinkimbi kakhulu: ukwenziwa kombhalo ogcwele, ukuhumusha kusuka kolunye ulimi kuya kolunye, ukudala isifinyezo, ukuphendula imibuzo, ukuhlukaniswa, ukukhipha ulwazi, njll. Ngokubonisa amaphethini olimi ezibalo, uhlelo lugcina luthuthukisa izethulo zangaphakathi ezicebile kakhulu ezibamba uhlelo lolimi, isitayela, kanye nobudlelwano phakathi kwemibono.
Ukuze kufezwe lokhu, amamodeli olimi aqeqeshwa nge iqoqo elikhulu lombhalo futhi bafunda ukulungisa amapharamitha abo angaphakathi ukuze basondeze izibikezelo zabo ezibonelweni zangempela. Inani lala mapharamitha (izisindo) yilokho esivame ukubhekisela kukho uma sikhuluma ngamamodeli anezigidi, izigidigidi, noma ngisho nezigidigidi zamapharamitha.
Umongo: kusukela kuma-n-gram kuya kumanethiwekhi e-neural
Isikhathi eside, indlela evame kakhulu yokwakha amamodeli olimi kwakuyi- amamodeli e-n-gramI-n-gram iwukulandelana okuhlelekile kwamagama angu-N: uma u-N=2 siwabiza ngokuthi ama-bigram; uma u-N=3, ama-trigram; njalo njalo. Isibonelo, ukuqala ngesisho esithi "umuhle kakhulu", ama-bigram angaba "uyi-", "uyi-very very", kanye "omuhle kakhulu".
Kusetshenziswa imodeli ye-trigram, uma inikezwe umongo wamagama amabili, uhlelo lubala amathuba egama ngalinye lesithathu elingenzeka kuye ngokuthi balubone kangaki lolo trigram ku-corpus yabo yokuqeqesha. Uma sibonile imisho eminingi yohlobo oluthi "orange is sealed" kanye nembalwa kakhulu yohlobo oluthi "orange is joyful", ukuqhubeka kokuqala kuzoba nesisindo esikhulu uma umongo uthi "orange is".
Inkinga ukuthi Umongo otholakalayo ulinganiselwe kakhulu.I-trigram ingabheka amagama amabili kuphela emuva, okuvame ukunganele ukuxazulula ukungaqondakali (isibonelo, ukuthi "i-orange" iyisithelo noma umbala) noma ukubamba ukuncika okude. Ukwandisa i-N kunikeza umongo owengeziwe, kodwa futhi kubhebhethekisa ukushoda kwedatha: amagremu angu-6 noma amagremu angu-7 avela kaningi kangangokuthi kunzima ukulinganisa amathuba athembekile.
Ukuze kunqotshwe lowo mkhawulo, kwafika okulandelayo amanethiwekhi e-neural aphindaphindiwe (RNN)Lezi zindlela zicubungula ithokheni yombhalo ngethokheni, zigcina isimo sangaphakathi esisebenza njengenkumbulo yomongo wangaphambilini. Izinhlobo ezifana ne-LSTM noma i-GRU zithuthukise ikhono lokugcina ulwazi isikhathi eside, okuvumela ukubanjwa kokuxhomekeka okude kunama-n-grams nokunciphisa amaphutha okubikezela emishweni eyinkimbinkimbi.
Kodwa-ke, ukuphathwa kwezinsiza zemvelo (i-NRM) kunezinkinga zako: imvelo ngokulandelana okuqinile Izindlela zabo zokucubungula zivimbela ukuhambisana futhi zenza ukuqeqeshwa kokulandelana okude kubize kakhulu futhi kuhambe kancane. Ngaphezu kwalokho, bahlushwa inkinga eyaziwayo ye... ukunyamalala kwe-gradientLokhu kunciphisa inani lomongo owusizo abangawusingatha ekusebenzeni. Lokhu kuhlanganiswa kwezithiyo kwashukumisa ukusesha izakhiwo ezintsha nezisebenza kahle.
Inguquko ye-Transformer kanye nendlela yokuzinakekela
Igxathu elikhulu langempela lafika Ukwakhiwa kwe-transformer, eyethulwe ngo-2017 esihlokweni esidumile esithi "Ukunaka yikho konke okudingayo". Le ndlela yakuyeka ngokuphelele ukuphinda ibuyele futhi yathembela endleleni ebalulekile: i ukuzinakekela (ukuzinaka), okuvumela imodeli ukuthi "ibheke" ngasikhathi sinye wonke amathokheni ngokulandelana futhi ilinganise ukuthi yiziphi izingxenye zomongo ezifanele kakhulu endaweni ngayinye.
Inqubo iqala nge uphawulapho umbhalo uhlukaniswa khona ube amathokheni (amagama, amagama angaphansi, njll.). Ithokheni ngayinye ihlelwe ku-vector yezinombolo ebizwa ngokuthi ukushumekaeqoqa ulwazi lwe-semantic kanye nolwe-syntactic. Lokhu kushumeka kudlula ezingqimbeni eziningi ze-Transformer, futhi kuzo zonke kuhlanzwa kancane kancane, kuba izethulo ezicebile zomongo ezifaka ulwazi mayelana nezinye izimpawu.
Ukuze imodeli ikwazi indawo yethokheni ngayinye, okulandelayo kuyangezwa: ukufaka ikhodi kwesimoLokhu kubonisa indawo yethokheni ngokulandelana futhi kuvumela ukuzinaka ukuhlukanisa phakathi, isibonelo, igama elivela ekuqaleni kanye nelifanayo elivela ekugcineni, okubalulekile ekuqondeni ukuhleleka kanye nesakhiwo semisho.
Ukuzinaka kusebenza ngokufaka iphrojektha ngayinye kumavektha amathathu ahlukene ngokusebenzisa ama-matrices esisindo afundiwe: imibuzo (Q), okhiye (K), kanye namanani (V). Umbuzo umelela lokho ithokheni "elikufunayo" kulo lonke uhlu, ukhiye ubonisa ulwazi "olunikezwa yithokheni ngayinye," futhi inani ulwazi oluzosakazwa lunesisindo ngokunaka.
Imodeli bese ibala izikolo zokuqondanisa njengokufana phakathi kombuzo ngamunye nazo zonke izinkinobho. Ngemva kokulungisa la maphuzu (isibonelo, nge-softmax), ithola izilinganiso zokunaka ezinquma ukuthi inani lethokheni ngalinye linikela kangakanani ekumelelweni okusha kwethokheni yamanje. Ngale ndlela, inethiwekhi igxila kalula kumongo ofanele futhi ishiye amathokheni angasizi ngalutho (njengamagama athile omsebenzi noma amagama angafanele endimeni ethile) ngemuva.
Enye yezinzuzo ezinkulu ze-Transformer ukuthi le ndlela isetshenziswa ku- kufanelana kakhuluNgokungafani nama-RNN, lapho amathokheni ecutshungulwa khona ngamunye ngamunye, lapha zonke izikhundla ezilandelanayo zicutshungulwa ngasikhathi sinye, okusheshisa kakhulu ukuqeqeshwa kwehadiwe yesimanje. Lokhu kuhlanganiswa komongo othe xaxa, ikhono elingcono lokubamba ukuncika okude, kanye nokusebenza kahle kokubala kuye kwavumela amamodeli ukuthi akhule abe ngosayizi ongacabangeki eminyakeni embalwa edlule.
Ayini ama-LLM (Amamodeli Olimi Olukhulu)?
Ngokusekelwe kuma-Transformers, okulandelayo kuye kwavela Amamodeli Olimi Olukhulu noma i-LLMamamodeli olimi amakhulu ngokoqobo. Lawa amanethiwekhi ajulile emizwa ana izigidi, izigidigidi, noma ngisho nezigidigidi zamapharamitha baqeqeshwe ngenani elikhulu lemibhalo evela ezincwadini, ezihlokweni, kumawebhusayithi, emibhalweni yobuchwepheshe kanye nezinye izinsiza zomphakathi (futhi ngezinye izikhathi ezizimele).
Lawa mamodeli asebenzisa ukufunda okujulile futhi aqeqeshwa kakhulu oziqondisayoEsikhundleni sokuthembela kudatha ebhalwe ngesandla, bafunda embhalweni ongabhalwanga, baxazulule imisebenzi yangaphakathi njengokubikezela igama elilandelayo noma ukugcwalisa izikhala emshweni. Ukusuka lapho, bathola ulwazi ngokungaqondile mayelana nohlelo lolimi, izilimi, amaqiniso omhlaba, izitayela zokubhala, izinqubo zokucabanga, kanye nezindlela zokuxoxa.
I-LLM yakudala iqeqeshwa ekuqaleni ngu ukufunda okungajwayelekile ukubikezela igama elilandelayo elinikezwe umongo. Kwezinye izimo, kwenziwa isigaba sesibili esifanayo, kwandiswe idatha noma kulungiswa umgomo wokuqeqesha ukuze kuthathwe kangcono umongo. Lokhu kuvame ukulandelwa isigaba se ukufunda okugadiwe noma of I-RLHF (Ukuqiniswa Ukufunda Empendulweni Yomuntu)lapho abachazi bezimpawu abangabantu behlola izimpendulo ezikhiqizwe, bamaka ukuthi yiziphi ezinhle noma ezimbi, futhi leso siginali sisetshenziselwa ukulungisa ukuziphatha kwemodeli.
Lokhu kuhlanganiswa kokulungiswa okukhulu kwangaphambi kokuqeqeshwa kanye nokuqeqeshwa kwangemva kokuqeqeshwa kuvumela ama-LLM ukuthi enze imisebenzi efana nalokhu ukuhumusha, ukubhala, ukufingqa, ingxoxo, ukwenziwa kwekhodi, noma ukuhlukaniswa ngokushelela okucishe kufane nokwabantu. Amathuluzi afana ne-ChatGPT, i-Claude, i-Gemini, i-Llama, kanye nezixazululo eziningi zebhizinisi athembele ngqo kulolu hlobo lwemodeli ukuze anikeze abasizi bengxoxo, izinhlelo zokusesha ezithuthukisiwe, noma ama-ejenti azimele asebenzisana nedatha yenkampani.
Kuhle ukugcizelela ukuthi, naphezu kokuhlakanipha kwabo okubonakalayo, i-LLM ayiqondi ulimi njengomuntu. Lokho abakwenzayo amaphethini ezibalo okulingisa futhi ubikezele ukuqhubeka okungenzeka kakhulu, yize izinga lobuchwepheshe linjalo kangangokuthi, ngezinjongo ezingokoqobo, umehluko uvame ukuba nzima ukuwuqonda empilweni yansuku zonke.
Ukuqeqeshwa kwe-LLM: idatha, izisindo, kanye nomsebenzi wokulahlekelwa
Ukuqeqeshwa kwe-LLM kuqala ngokuqoqwa kanye nokulungiswa kwe-a isethi yedatha enkuluLe datha iyalungiswa, ihlungwe ukuze kususwe umsindo, bese ibekwa uphawu. Izisindo zemodeli ziyaqalwa, bese kuchazwa umsebenzi wokulahlekelwa ukuze kulinganiswe iphutha phakathi kwezibikezelo kanye nochungechunge lokuqeqeshwa kwangempela.
Izinyathelo zokuqeqesha ezingaphezu kwezigidi noma ngisho nezigidigidi, imodeli yenza izibikezelo zethokheni ngethokheni futhi umsebenzi wokulahlekelwa ulinganisa ukuthi ukude kangakanani nokulandelana okufanele. Ukusebenzisa ama-algorithms afana nokwehla kwe-gradient kanye ukusabalalisa emuvaIzisindo zilungiswa ungqimba ngengqimba ku-iteration ngayinye ukuze kuncishiswe leli phutha. Ngale ndlela, ama-matrices akhiqiza imibuzo yokuzisiza, okhiye, kanye namanani, kanye nokubikezelwa kokushumeka, asebenzisa ukucushwa okuwusizo kakhulu.
Kule nqubo imodeli ifunda ukuhlanganiswa kwencazelo: amathokheni anjengelithi "inja" kanye nelithi "ikhonkotha" agcina ekhona vala isikhala sevektha lapho umongo ubhekisela ezifuyweni, kuyilapho elithi "igxolo" kanye nelithi "umuthi" libonakala lingahlobene kangako. Lesi sikhala sokushumeka sibamba ukufana ngencazelo, ukufaniswa, kanye nobudlelwano phakathi kwemibono esetshenziswa emisebenzini elandelayo.
Uma ukuqeqeshwa kwangaphambi kokuqeqeshwa sekuqediwe, ukuhleleka Kwayo ngamasethi edatha aqondile kakhulu ukuqondisa imodeli emisebenzini eqondile: ukulandela imiyalelo, ukuphendula imibuzo ngenhlonipho, ukuhlonipha izindlela ezithile zokuphepha, ukwamukela ithoni ethile, njll. Kumamodeli okuxoxa njenge-GPT-4, lesi sigaba sivame ukuhambisana ne-RLHF, lapho abantu kanye nezinye izinhlobo ngezinye izikhathi behlola iziphakamiso zempendulo futhi basize ekuqondiseni uhlelo ekuziphatheni okuwusizo nokuphephile.
Umphumela wokugcina uyimodeli efakwe ngaphakathi amaphethini ohlelo lolimi, ulwazi lwamaqiniso, izakhiwo zokucabanga, kanye nezitayela isatshalaliswa kuwo wonke amapharamitha ayo. Uma ithola okokufaka okusha, ingakhiqiza imiphumela ehambisanayo, evumelana nomongo, futhi, ezimweni eziningi, imiphumela yokudala.
I-GPT, i-ChatGPT kanye nobudlelwano bayo nama-LLM
Leli gama I-GPT Isifinyezo simelela "i-Generative Pre-trained Transformer." Sibhekisela emndenini othize wama-LLM athuthukiswe yi-OpenAI osekelwe ngqo kusakhiwo se-Transformer. Igama elithi "Generative" libonisa ikhono layo lokukhiqiza okuqukethwe okusha, elithi "Pre-trained" libhekisela eqinisweni lokuthi iqeqeshwa kuma-corpora amakhulu ngaphambi kokujwayela imisebenzi ethile, kanti elithi "Transformer" libhekisela kusakhiwo esiyisisekelo.
I-ChatGPT Empeleni, uhlelo lokusebenza lwengxoxo olwakhelwe kumamodeli e-GPT (njenge-GPT-4 kanye nezinhlobo zayo). I-LLM isebenza "njengobuchopho" obukhiqiza izimpendulo, kuyilapho isikhombimsebenzisi se-ChatGPT siwungqimba oluvumela abasebenzisi ukuthi baxoxe kalula nalolo hlobo. Ngaphandle kwemodeli yolimi eyisisekelo, i-ChatGPT ibingaba yibhokisi lombhalo elingenalutho elingenawo amakhono okukhiqiza.
Umehluko phakathi kwe-GPT ne-LLM ungaqondwa kanje: I-LLM iyisigaba esijwayelekile okuhlanganisa noma yiluphi uhlobo lolimi olukhulu; i-GPT iwumndeni othize ngaphakathi kwaleso sigaba. Ezinye izibonelo zama-LLM angewona ama-GPT yiClaude (Anthropic), Gemini (Google), Llama (Meta), Mistral, noma amamodeli avulekile njenge-BLOOM.
Izinhlobo zamamodeli olimi kanye nemindeni evelele
Ngaphakathi kwesimiso sezinto samanje kukhona okuningi izinhlobo ze-LLM kanye namamodeli olimi, ngalinye linezinhloso nezici ezihlukile. Amanye aklanyelwe imisebenzi ejwayelekile, amanye ukuqonda umongo ngokujulile, amanye ukukhiqiza ikhodi, kanti amanye enzelwe izizinda ezikhethekile kakhulu.
Phakathi kwamamodeli ajwayelekile ahloselwe ukukhiqiza umbhalo nengxoxo, okulandelayo kuyaphawuleka: I-GPT-3/GPT-4 kusuka ku-OpenAI, Claude kusukela ku-Anthropic, amamodeli Isundu kanye neGemini kusuka ku-Google, kanye nomndeni Llama I-Meta, ebilokhu iyisishayeli esikhulu se-open source ecosystem. Amapulatifomu amaningi ebhizinisi anikeza ama-hub lapho ungakhetha khona kwamanye alawa mamodeli kuye ngokuthi ukusetshenziswa, izindleko, ukubambezeleka, kanye nemikhawulo yobumfihlo.
Emkhakheni we ukuqonda ulimiamamodeli afana ISITOLO Imibono ye-Bidirectional Encoder evela ku-Transformers (BERT) iphawule iphuzu lokushintsha. I-BERT iqeqeshwe ngokwezinhlangothi ezimbili, okusho ukuthi ifunda ukubikezela amagama afihliwe isebenzisa umongo odlule nolandelayo, okuvumela ukuthi ibambe kangcono ama-nuances kanye nobudlelwano obuyinkimbinkimbi ngaphakathi komusho. Izinhlobo ezifana ne-DistilBERT, i-RoBERTa, i-ALBERT, kanye ne-XLM-R zithuthukisa ukusebenza, usayizi, noma ukwesekwa kwezilimi eziningi.
Ngokuba ukukhiqizwa kwekhodi Kunamamodeli afana ne-Codex (isisekelo se-GitHub Copilot) noma i-AlphaCode, aqeqeshwe ngokukhethekile ezindaweni zokugcina izinhlelo kanye nezinkinga ze-algorithmic. Lezi zinhlelo ziyakwazi ukuphakamisa imisebenzi, ukuqeda amabhlogo ekhodi, noma ngisho nokuxazulula izivivinyo eziyinkimbinkimbi ezivela ezincazelweni zolimi lwemvelo.
Emhlabathini izilimi eziningi kanye nezinhlobo eziningi Sithola iziphakamiso ezifana ne-BLOOM, CLIP, noma izinhlelo zesimanje ze-GPT, ezikwazi ukusebenza ngombhalo, izithombe, umsindo, ngisho nevidiyo. Umkhuba ocacile ubheke kumamodeli ahlanganisa izindlela eziningana ngasikhathi sinye, avula umnyango wezinhlelo zokusebenza ezifana nokuhlaziywa kwevidiyo nencazelo yombhalo, abasizi abaqonda imidwebo, noma izinhlelo ezihlanganisa ulwazi olubonakalayo nolombhalo; kukhona ngisho amamodeli ezwi kanye ne-multimodal njenge-MAI Voice 1 okubonisa lokhu kuthuthuka.
Ekugcineni, okulandelayo kuye kwanda isisindo: ama-LLM amancane noma asebenzayoYakhelwe ukusebenza kumadivayisi ancishisiwe izinsiza (eselula, emaphethelweni, njll.) noma ukunciphisa izindleko zokuqagela, izinguqulo ezincishisiwe ze-Llama, T5, ALBERT, noma amanye amamodeli zivumela ukuthunyelwa kwamakhono e-AI okukhiqiza ngaphandle kokudinga ingqalasizinda enkulu yamafu.
I-LLM vs. I-NLP Yendabuko
Kuvamile ukudida imiqondo I-LLM kanye ne-NLPUkucubungula Ulimi Lwemvelo (i-NLP) yinkambu ebanzi ehlanganisa zonke izindlela zokucubungula ulimi ngokuzenzakalelayo: ukuhlaziywa kwemizwa, ukukhishwa kwento, ukutholwa kwesihloko, ukuhumusha, ukufingqa, njll. Ngokomlando, yonke yale misebenzi yaxazululwa nge amamodeli athile okuqeqeshwe ngokungahleliwe: ama-algorithms ezibalo, izinhlelo ezisekelwe emithethweni, amamodeli e-n-gram, amanethiwekhi e-LSTM, i-word2vec, njll.
Ama-LLM amelela ukuvela kwe-NLP yendabuko. Esikhundleni sokuqeqesha imodeli ehlukile yomsebenzi ngamunye, imodeli eyodwa enkulu, enenhloso ejwayelekile ingenza ukuhumusha, ukufingqa, ukuhlukaniswa, ukukhiqiza umbhalo, ukucabanga okuyisisekelo, kanye neminye imisebenzi eminingi ngaphandle kokuqeqeshwa okwengeziwe noma ngokulungiswa okuncane kakhulu (okwaziwa ngokuthi i-zero-shot kanye nokufunda kwe-few-shot).
Umehluko oyinhloko uku isikali kanye nendlela yokwenzaNakuba amamodeli e-NLP akudala aqeqeshwe kumasethi edatha amancane, anelebula, ama-LLM afunda kuma-trillion amathokheni angenalebula, ebamba amaphethini acebile kakhulu. Lokhu akusho ukuthi i-NLP isiphelelwe yisikhathi; kunalokho, ama-LLM aseyizibonelo eziyisisekelo lapho izixazululo ezithile ze-NLP zakhiwe khona ezimweni zangempela.
Ukusetshenziswa okungokoqobo kwamamodeli olimi
Namuhla, ama-LLM ayinsika yezinhlobonhlobo ezinkulu ze- izinhlelo zokusebenza nemikhiqizoEmkhakheni wabasizi ababonakalayo, bakhuthaza amathuluzi anjenge-Siri, i-Google Assistant, i-Alexa, noma ama-chatbot ewebhu aqonda izicelo ngolimi lwemvelo futhi abuyisele izimpendulo ezifanele, enze imiyalo, noma enze izenzo ezifana nokuthumela imiyalezo nokuhlela ama-aphoyintimenti.
Ekuhumusheni komshini, amamodeli athuthukile avumela ukuhumusha imibhalo ngokunembe kakhudlwana nangokwemvelo kunezinhlelo ezisekelwe emithethweni yakudala. Amapulatifomu afana ne-Google Translate noma i-DeepL athuthukise ikhwalithi yawo ngokusobala ngenxa yezakhiwo zohlobo lwe-Transformer eziqeqeshwe ngedatha enkulu yezilimi eziningi.
Ekukhiqizeni, amamodeli olimi ahlanganiswe abahloli bohlelo lolimi nesitayelaIzici zokuqedela ngokuzenzakalela kumadivayisi eselula kanye nama-word processors, iziphakamiso zokusesha kuziphequluli namafomu, kanye nezinhlelo zokukhiqiza okuqukethwe kwezokuxhumana, amabhulogi, noma imikhankaso yokukhangisa. Uma ufuna ukufunda ukuthi kanjani Sebenzisa ubuhlakani bokwenziwa kumadokhumenti akhoKuneziqondiso ezisebenzayo ezibonisa indlela yokusebenzisa le misebenzi kubahleli banamuhla.
Emkhakheni webhizinisi, ama-LLM ajwayele zenzeka ngokuzenzakalelayo isevisi yamakhasimende ngama-chatbot akwazi ukuxazulula imibuzo evame ukubuzwa, ukudala izifinyezo eziphezulu zemibhalo yangaphakathi, ukusiza ukubhala imibiko, ukukhiqiza ikhodi emaqenjini okuthuthukisa, noma ukusiza ngemisebenzi yokuphatha ephindaphindwayo. Amasu afana ne-RAG (Retrieval-Augmented Generation) avumela imodeli ukuthi ixhunywe ezisekelweni zolwazi lwangaphakathi ukuze izimpendulo zisekelwe olwazini oluqinisekisiwe nolusesikhathini.
Kukhona nama-LLM okukhethekile ngesizindaIzibonelo zifaka phakathi i-BioBERT yocwaningo lwezokwelapha, i-FinBERT yemibhalo yezezimali, kanye ne-LegalBERT yemibhalo yezomthetho. Lawa mamodeli ahlungwa kumabhizinisi athile ukuze kuthuthukiswe ukunemba emkhakheni wawo futhi asekele odokotela, abameli, noma abahlaziyi ekufundeni nasekuhlanganiseni ulwazi oluningi.
Izinzuzo, ubuthakathaka, kanye nezinselele zokuziphatha
Amamodeli ezilimi ezinkulu anikeza izinzuzo ezicacile: ukwenza imisebenzi eyisicefe ngokuzenzakalelayoZandisa umkhiqizo, zivumela ukudalwa kwabasizi bezingxoxo zemvelo, zilula ukuhumusha, zisheshise izinhlelo, futhi zenze kube lula ukufinyelela olwazini oluyinkimbinkimbi. Ziyithonya eliphazamisayo elifana nokusetshenziswa kwamarobhothi embonini, kodwa lisetshenziswa emsebenzini wolwazi.
Nokho, baphethe uchungechunge lwe- ukulinganiselwa okukhuluEzaziwa kakhulu yi-"hallucinations": imodeli ingakhiqiza izimpendulo ezizwakala zikholisa kakhulu kodwa zingamanga noma zinganembile. Ngenxa yokuthi ifunda ngokuhlobana kwezibalo hhayi ngokuqonda okujulile komhlaba, ingasungula izingcaphuno, idatha, noma izinkomba ezingakaze zibe khona.
Enye inselele eyinhloko yi- ukuchemaAma-LLM athola ubandlululo lwamasiko, imibono engafani, noma amaphethini okubandlulula avela kudatha yokuqeqesha, okungaholela ezimpendulweni eziyinkinga uma kungahlungwa futhi kungalungiswa. Ngaphezu kwalokho, aphakamisa izinkinga zobumfihlo kanye nokuhambisana nomthetho lapho kusetshenziswa idatha ebucayi, ikakhulukazi uma isetshenziswa ngama-API angaphandle kunengqalasizinda yobunikazi.
El izindleko zokubala Izindleko zokuqeqesha nokusebenzisa amamodeli amakhulu ziphezulu kakhulu, kokubili ngokwezomnotho kanye namandla. Lokhu kudala impikiswano mayelana nokusimama kanye nokuqoqwa kwamandla obuchwepheshe ezinkampanini ezimbalwa ezinekhono lokuqeqesha amamodeli esizukulwane esilandelayo.
EYurophu nakwezinye izifunda, izinhlaka zomthetho ezifana ne- Isenzo se-AI Bafuna ukucaca, ukuhlolwa kwengozi, kanye nokubhekwa kwabantu, ikakhulukazi ezinhlelweni ezisebenzisana nabathengi noma ezenza izinqumo ezinomthelela omkhulu. Ngaphezu kwalokhu ingozi yokuvalelwa kwabathengisi, into izinkampani eziningi ezizama ukuyinciphisa ngokuhlola amamodeli avulekile namasu ahlanganisiwe.
Indlela ama-LLM aklanywa futhi alungiswa ngayo ngokusebenza
Ngokombono wobunjiniyela, ukudala nokusebenzisa i-LLM kuhilela ukulandela uchungechunge lwezindlela izigaba ezibalulekileOkokuqala, inhloso iyachazwa: ingabe ufuna imodeli yenhloso ejwayelekile, umsizi wokusekela ubuchwepheshe, uhlelo lokuhlaziya kwezomthetho, noma i-AI yokumaketha nokuthengisa? Lesi sinqumo siqondisa ukuthi yiluphi ulwazi olukhethiwe nokuthi ukusebenza kuzohlolwa kanjani.
Bese kubhekwana nalokhu okulandelayo ngaphambi kokujimaLokhu kuhilela ukuqoqa nokulinganisa isethi yedatha enkulu nehlukahlukene. Umbhalo ube usubekwa uphawu, bese kuchazwa ukwakheka (inani lezendlalelo, usayizi wokushumeka, inani lamakhanda okunaka, njll.). Ukukhetha ingqalasizinda kubalulekile: amaseva asebenza kahle anama-GPU amaningi noma ama-TPU, noma amaqoqo amafu akwazi ukusingatha imithwalo yemisebenzi emikhulu, ayadingeka.
Ngesikhathi sokuqeqeshwa, kwenziwa izinguquko ama-hyperparameters njengesilinganiso sokufunda, usayizi weqembu, inani lezinyathelo, amasu okuqondisa kabusha, kanye nezinhlelo zokuhlela ukufunda. Uma lesi sigaba sesiphelile, ukulungiswa kahle kuqala, lapho imodeli ihlungwa khona ngokuphindaphindiwe ngedatha ethile, izilinganiso zekhwalithi, kanye, ezimweni eziningi, ukuhlolwa kwabantu.
Ekusetshenzisweni kwangempela, ochwepheshe abaningi abaqeqeshi amamodeli kusukela ekuqaleni, kodwa bathembele ku- Ama-LLM asevele eqeqeshwe kusengaphambili ezinikezwa izinhlangano ezinkulu noma umphakathi ovulekile. Basebenzisa amasu anjengokulungisa okulula, ubunjiniyela obusheshayo, i-RAG, noma i-distillation ukuze bazivumelanise nomongo wazo, banciphise izindleko, futhi bathuthukise ukusebenza kahle kokukhiqiza.
Ngaphakathi kwalolu hlelo olubanzi, ama-LLM ayacatshangelwa amamodeli wokusungulaAmanethiwekhi amakhulu, ajwayelekile lapho kwakhiwa khona izixazululo eziqondile. Ukuzivumelanisa nezimo kwawo, kanye nokuthuthuka okusheshayo kwezinguqulo eziningi nezisebenza kahle, kukhomba ikusasa lapho amathuluzi afinyeleleka kalula azovumela izinkampani nabasebenzisi ukuthi basebenzise i-AI ekhiqizayo nsuku zonke.
Lesi simo sonke sisho ukuthi amamodeli olimi asuke ekubeni yilukuluku lokucwaninga afinyelela ekubeni yi- ingqalasizinda eyisisekelo yomnotho wedijithali: sebevele baguqula isevisi yamakhasimende, ukumaketha, ukuthuthukiswa kwesofthiwe, ucwaningo, kanye nendlela esisebenzisana ngayo nobuchwepheshe. Ukuqonda ukuthi basebenza kanjani, ukuthi bangenzani, nokuthi bahluleka kuphi kubalulekile ekusebenziseni izinzuzo zabo ngenkathi behlala beqaphela izingozi zabo kanye nemikhawulo yabo.
