Uhlolojikelele
Esikhundleni sokubikezela ithokheni elandelayo nje, imodeli iqeqeshelwe ukubikezela amathokheni amaningana esikhathi esizayo ngesikhathi esisodwa. Lokhu kucija amasiginali okufunda futhi kuvule ukucatshangelwa okusheshayo ngokuziqopha ngokuzicabangela wena.
I-Multi-Token Prediction Training iyingxenye yesitaki solimi-AI esisetshenziselwa ukufunda, ukukhiqiza, ukuhlukanisa, nokuguqula umbhalo nenkulumo ngesilinganiso.
I-Deep Dive
Amamodeli olimi ajwayelekile aqeqeshwa ngokubikezela kwethokheni elandelayo: uma kunikezwe umongo, bikezela ithokheni eyodwa elandelayo. I-Multi-token prediction (MTP), eyaduma ngephepha lango-2024 Meta futhi yamukelwa ku-DeepSeek-V3, ingeza amakhanda okukhiphayo angasindi engeziwe ukuze imodeli ibikezele kanyekanye ithokheni elandelayo kanye ne-2nd, 3rd, kanye nethokheni yesi-4 ngaphambili kusukela kusimo esifihliwe esifanayo. Lokhu kuphoqa inethiwekhi ukuthi ihlele ngokuqhubekayo esikhathini esizayo futhi igxilisa isignali yokuqeqesha - indawo ngayinye manje inikela ngemibandela yokulahlekelwa eminingi. Meta ibike izinzuzo ezinkulu ikakhulukazi ekubhaleni ngekhodi nokucabanga okukhiqizayo, ngamamodeli amakhulu azuza kakhulu. Okubaluleke kakhulu, amakhanda engeziwe angalahlwa ngemuva kokuqeqeshwa, ngakho-ke usayizi wemodeli ekusetshenzisweni akufanele ukhule.
I-Technical Insight
I-MTP inamathisela n amakhanda okubikezela okuzimele phezu kwe-trunk ye-transformer eyabiwe; inhloko k ibikezela ithokheni endaweni t+k kusukela ekumeleleni endaweni t. Ukulahlekelwa kufingqwa ngesikhathi sokuqeqeshwa. Uma kucatshangelwa, amakhanda asizayo anika amandla ukuzichaza ngokwakho: imodeli ihlongoza amathokheni amaningana kuphasi eyodwa, bese iyawaqinisekisa, ifinyelele cishe kusizukulwane esisheshayo esingu-3x ngaphandle kokushintsha ukusatshalaliswa kokuphumayo.
Ukuthola Ukuqeqeshwa Kwezibikezelo Zezimpawu Eziningi
Esikhundleni sokubikezela ithokheni elandelayo nje, imodeli iqeqeshelwe ukubikezela amathokheni amaningana esikhathi esizayo ngesikhathi esisodwa. Lokhu kucija amasiginali okufunda futhi kuvule ukucatshangelwa okusheshayo ngokuziqopha ngokuzicabangela wena. I-Multi-Token Prediction Training iyingxenye yesitaki solimi-AI esisetshenziselwa ukufunda, ukukhiqiza, ukuhlukanisa, nokuguqula umbhalo nenkulumo ngesilinganiso. Ukuze wakhe ukuqonda okujulile, phatha i-Multi-Token Prediction Training njengemodeli yokusebenza, hhayi isici esisodwa: chaza imiphumela efiselekayo, ucacise ukucabanga, futhi uhlukanise lokho uhlelo olungakwenza ngokwethembeka kulokho okusadinga ukwahlulela kochwepheshe.
Empeleni, amaqembu aqinile asebenzisa i-Multi-Token Prediction Training ukwazisa, ukubuyisa, nokubuyekeza ama-loops njengohlelo olulodwa lokuxhumana oludidiyelwe. Babhala imibandela yempumelelo ecacile, ukuhlola okuqhathaniswa nedatha engokoqobo nokugeleza komsebenzi, futhi baphindaphinde ngokusekelwe kumaphethini okuhluleka aqashiwe esikhundleni sokuwina kwebhentshimakhi yesikhathi esisodwa. Yilapho ukuqonda kwethiyori kuguquka kube amandla ahlala njalo kuwo wonke umkhiqizo, inqubomgomo, kanye nokusebenza.
Ukugeleza komsebenzi wolimi kungahamba ngokushesha ngaphandle kokudela ukuvumelana. Ngesikhathi esifanayo, amaqiniso Akhohliwe angafaka imibiko buthule, ukugeleza kosekelo, noma imiphumela yocwaningo. Indlela eqine kakhulu iwukuhlanganisa isivinini sokuhlola nesiyalo sokuphatha: qhuba abashayeli bezindiza, bamba ubufakazi, ushicilele amalogi ezinqumo, futhi ubuyekeze izivikelo ngokuqhubekayo njengoba imodeli yokuziphatha, okulindelwe ngabasebenzisi, kanye nezimfuneko zokulawula zishintsha.
I-Strategic Impact
Ukugeleza komsebenzi wolimi kungahamba ngokushesha ngaphandle kokudela ukuvumelana.
Ukugeleza komsebenzi wolimi kungahamba ngokushesha ngaphandle kokudela ukuvumelana. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Yandisa ukufinyelela kuzo zonke izilimi nezitayela zokuxhumana.
Yandisa ukufinyelela kuzo zonke izilimi nezitayela zokuxhumana. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Amaqembu angachitha isikhathi esiningi ekwahluleleni kuyilapho i-automation isingatha impinda.
Amaqembu angachitha isikhathi esiningi ekwahluleleni kuyilapho i-automation isingatha impinda. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Ukuqaliswa Komhlaba Wangempela
I-DeepSeek-V3 isebenzisa inhloso ye-MTP ngesikhathi sokuqeqeshwa kusengaphambili ukuze kukhuliswe ukusebenza kahle kwedatha futhi inike amandla ukuqopha okucatshangelwayo
Meta amamodeli wokukhiqiza ikhodi abonisa izinzuzo zokunemba ku-HumanEval kanye ne-MBPP kusukela ekubikezeleni amathokheni amaningi
Ukuqopha okucabangelayo: ukubhala amathokheni angu-3-4 ngokudlula phambili ngakunye bese kuqinisekisa ukuphuma okusheshayo, okugcina ukusabalalisa
Ukuqedela ngokuzenzakalela ngokushesha kubasizi bokubhala amakhodi lapho kuhlongozwa amathokheni amaningi abambekayo futhi ahlolwe ngesinyathelo esisodwa
Amaphethini Okusebenzisa
I-Multi-Token Prediction Training in practice
I-DeepSeek-V3 isebenzisa umgomo we-MTP phakathi nokuqeqeshwa kusengaphambili ukuze kuthuthukiswe ukusebenza kahle kwedatha futhi inike amandla ukuqopha okucatshangelwayo.
I-DeepSeek-V3 isebenzisa umgomo we-MTP phakathi nokuqeqeshwa kusengaphambili ukuze kuthuthukiswe ukusebenza kahle kwedatha futhi inike amandla Amathimba okuqagela okuqagelayo ngokuvamile athola imiphumela engcono lapho echaza imingcele yekhwalithi ngaphambili, egcina indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-Multi-Token Prediction Training in practice
Meta amamodeli okukhiqiza ikhodi abonisa izinzuzo zokunemba ku-HumanEval kanye ne-MBPP kusukela ekubikezeleni amathokheni amaningi.
Meta amamodeli okukhiqiza amakhodi abonisa izinzuzo zokunemba ku-HumanEval kanye ne-MBPP kusukela ekubikezeleni amathokheni amaningi Amathimba ngokuvamile athola imiphumela engcono uma echaza imikhawulo yekhwalithi ngaphambili, egcina indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-Multi-Token Prediction Training in practice
Ukubhala amakhodi okucabangela ngokwakho: ukubhala amathokheni angu-3-4 ngephasi ngayinye eya phambili bese kuqinisekisa ukuphuma okusheshayo, okugcina ukusabalalisa.
Ukubhala amakhodi okucabangela wena ngokwakho: ukubhala amathokheni angu-3-4 ngephasi ngayinye eya phambili bese kuqinisekisa ukuphuma okukhiphayo okusheshayo, okugcina ukusatshalaliswa Amathimba ngokuvamile athola imiphumela engcono uma echaza imingcele yekhwalithi ngaphambili, agcina indlela yokukhuphuka komuntu ngamacala asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-Multi-Token Prediction Training in practice
Ukuqedela ngokuzenzakalela okusheshayo kuzisizi zokubhala amakhodi lapho amathokheni amaningi abambekayo ehlongozwayo futhi ahlolwe ngesinyathelo esisodwa.
Ukuqedela ngokuzenzakalelayo ngokushesha kubasizi bokubhala amakhodi lapho kuhlongozwa amathokheni amaningi abambekayo futhi ahlolwe esinyathelweni esisodwa Amathimba ngokuvamile athola imiphumela engcono lapho echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
Izingozi & Guardrails
Amaqiniso akhonjiwe angafaka ngokuthula imibiko, ukugeleza kosekelo, noma imiphumela yocwaningo.
Ukuzwela okusheshayo kungadala imiphumela engahambisani kuzo zonke izicelo ezifanayo.
Idatha yombhalo ebucayi ingase idalulwe uma izilawuli zokufinyelela zibuthakathaka.
Ukuqalisa Umhlahlandlela
Chaza ifomethi yokuphumayo, ithoni, namazinga wekhwalithi ngaphambi kokukhishwa.
Chaza ifomethi yokuphumayo, ithoni, namazinga wekhwalithi ngaphambi kokukhishwa. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Izimpendulo eziyisisekelo ngemithombo ethembekile noma nini lapho ukunemba kubalulekile.
Izimpendulo eziyisisekelo ngemithombo ethembekile noma nini lapho ukunemba kubalulekile. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Gcina indawo yokuhlola isibuyekezo somuntu ukuze uthole imiphumela ephezulu.
Gcina indawo yokuhlola isibuyekezo somuntu ukuze uthole imiphumela ephezulu. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Landela amaphethini okuhluleka futhi uqeqeshe kabusha imiyalo noma ukuhamba komsebenzi njalo.
Landela amaphethini okuhluleka futhi uqeqeshe kabusha imiyalo noma ukuhamba komsebenzi njalo. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.