Dubawa
Multi-Head Latent Attention (MLA) wani tsarin kulawa ne, wanda aka gabatar a cikin DeepSeek-V2, wanda ke matsar da maɓalli-ƙimar maɓalli na yunwar ƙwaƙwalwar ajiya a cikin ƙaramin ɓoyayyen ɓoyayyen ɓoyayyen ɓoyayyiya. Yana ba da damar manyan samfuran harshe suyi aiki tare da ƙarancin ƙwaƙwalwar GPU mai nisa yayin kiyaye inganci kusa da daidaitaccen kulawa.
Hankalin Latent Mai-Head wani ɓangare ne na tarin yare-AI da ake amfani da shi don karantawa, ƙirƙira, rarrabuwa, da canza rubutu da magana a sikeli.
Zurfafa nutsewa
Lokacin da taswirar ta samar da rubutu, tana adana maɓalli da ƙima ga kowane alamar da ta gabata a cikin 'KV cache.' Wannan cache yana girma tare da tsawon mahallin kuma yana mamaye amfani da ƙwaƙwalwar ajiya yayin ƙaddamarwa. MLA tana maye gurbin manyan manyan maɓalli/ƙimar ƙima tare da ƙaramin madaidaicin madaidaicin sikelin kowane alama, sannan ayyukan da ke ɓoye baya zuwa maɓallan kowane kai da ƙima akan tashi. Saboda ƙananan latent ɗin kawai aka adana, DeepSeek-V2 ya ba da rahoton yanke ƙwaƙwalwar ajiyar KV-cache sama da 90% tare da daidaitaccen kulawar kai mai yawa, yana ba da damar yanayi mai tsayi da girma girma. Mahimmanci, za a iya naɗe matrices masu haɓakawa zuwa wasu ma'auni, don haka MLA ta cimma wannan matsawa tare da ƙaramin ko asara mai ƙima a cikin ingancin ƙirar ƙira.
Fahimtar Fasaha
MLA tana aiwatar da matsawar haɗin gwiwa mai ƙarancin daraja: kowane ɓoyayyen yanayin alama ana ƙididdige shi zuwa ƙarami mai ɓoyayyiyar ɓoyayyiyar ɓarna, da keɓance matrices masu tasowa suna sake gina maɓallan kowane kai da ƙima. Dabarar wayo ita ce 'ɗaukar' ma'aunin ƙima a cikin tambaya da tsinkayar fitarwa, don haka ƙirar ba ta taɓa samun cikakkun maɓalli/daraja yayin zayyana ba. Ana amfani da abubuwan sakawa na rotary tare da hanyar da aka yanke, tunda ba za'a iya juyar da jujjuya iri ɗaya ba, adana bayanan matsayi.
Jagoran Hankalin Latent Multi-Head
Multi-Head Latent Attention (MLA) wani tsarin kulawa ne, wanda aka gabatar a cikin DeepSeek-V2, wanda ke matsar da maɓalli-ƙimar maɓalli na yunwar ƙwaƙwalwar ajiya a cikin ƙaramin ɓoyayyen ɓoyayyen ɓoyayyen ɓoyayyiya. Yana ba da damar manyan samfuran harshe suyi aiki tare da ƙarancin ƙwaƙwalwar GPU mai nisa yayin kiyaye inganci kusa da daidaitaccen kulawa. Hankalin Latent Mai-Head wani ɓangare ne na tarin yare-AI da ake amfani da shi don karantawa, ƙirƙira, rarrabuwa, da canza rubutu da magana a sikeli. Don gina zurfin fahimta, bi Multi-Head Latent Attention a matsayin samfurin aiki, ba fasali ɗaya ba: ayyana sakamakon da ake so, fayyace zato, da raba abin da tsarin zai iya yi da dogaro daga abin da har yanzu yana buƙatar yanke hukunci na ƙwararru.
A aikace, ƙungiyoyi masu ƙarfi ta amfani da Multi-Head Latent Attention ƙira ta sawa, dawo da, da sake duba madaukai azaman tsarin sadarwar haɗin gwiwa ɗaya. Suna rubuta ƙayyadaddun ƙa'idodin nasara, gwaji akan bayanan gaskiya da gudanawar aiki, da jujjuyawar bisa ga tsarin gazawar da aka lura maimakon cin nasara na lokaci ɗaya. Wannan shine inda fahimtar ka'idar ta juya zuwa iyawa mai dorewa a cikin samfura, manufofi, da ayyuka.
Gudun aikin harshe na iya tafiya da sauri ba tare da sadaukar da daidaito ba. A lokaci guda, abubuwan da ba a iya gani ba na iya shigar da rahotanni cikin nutsuwa, kwararar goyan baya, ko abubuwan bincike. Hanyar da ta fi dacewa ita ce haɗa saurin gwaji tare da horon gudanarwa: gudanar da matukin jirgi, kama shaida, buga rajistan ayyukan yanke shawara, da ci gaba da sabunta abubuwan tsaro kamar yadda halayen ƙira, tsammanin mai amfani, da buƙatun tsari ke tasowa.
Dabarun Tasiri
Gudun aikin harshe na iya tafiya da sauri ba tare da sadaukar da daidaito ba.
Gudun aikin harshe na iya tafiya da sauri ba tare da sadaukar da daidaito ba. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Yana faɗaɗa damar shiga cikin harsuna da salon sadarwa.
Yana faɗaɗa damar shiga cikin harsuna da salon sadarwa. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Ƙungiyoyi za su iya ciyar da ƙarin lokaci akan hukunci yayin da aiki da kai ke sarrafa maimaitawa.
Ƙungiyoyi za su iya ciyar da ƙarin lokaci akan hukunci yayin da aiki da kai ke sarrafa maimaitawa. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Aiwatar da Gaskiyar Duniya
Hidimar DeepSeek-V2/V3 ƙirar hira tare da ƙaramin sawun ƙwaƙwalwar GPU mai ban mamaki ga kowane buƙatu
Gudun dogon-takardun tambaya yana amsawa inda babban ma'ajin KV zai shayar da VRAM
Haɓaka girman batch ɗin ƙima akan ƙayyadaddun GPU saboda kowane jeri yana adana ɗan ƙaramin vector ne kawai
Bayar da dogon mahallin windows akan kayan masarufi don mataimakan da aka haɓaka
Hanyoyin Aiwatarwa
Multi-Head Latent Hankali a aikace
Hidimar DeepSeek-V2/V3 ƙirar hira tare da ƙaramin sawun ƙwaƙwalwar GPU mai ban mamaki ga kowane buƙatu.
Hidimar DeepSeek-V2/V3 ƙirar hira tare da ƙarami ƙananan sawun ƙwaƙwalwar GPU a kowace buƙata Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.
Multi-Head Latent Hankali a aikace
Gudun dogon-takardun tambaya yana amsawa inda babban ma'ajin KV zai shayar da VRAM.
Gudanar da dogon-takardun tambaya yana amsa inda babban cache na KV in ba haka ba zai ƙare ƙungiyoyin VRAM yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ƙofofin inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin duk nasarorin samarwa da farashi na kuskure akan lokaci.
Multi-Head Latent Hankali a aikace
Haɓaka girman batch ɗin ƙima akan ƙayyadaddun GPU saboda kowane jeri yana adana ɗan ƙaramin vector ne kawai.
Haɓaka girman batch akan GPU ɗin da aka gyara saboda kowane jeri yana adana ƙananan ƙungiyoyin ɓoyayyiyar ɓoyayyiya yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.
Multi-Head Latent Hankali a aikace
Bayar da dogon mahallin windows akan kayan masarufi don mataimakan da aka haɓaka.
Bayar da dogon mahallin windows akan kayan masarufi don mataimakan maidowa Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ƙofofin inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin duk nasarorin samarwa da farashi na kuskure akan lokaci.
Hatsari & Tsare-tsare
Abubuwan da aka ruɗe suna iya shigar da rahotanni cikin nutsuwa, kwararar tallafi, ko abubuwan bincike.
Hankali na gaggawa na iya ƙirƙirar sakamako mara daidaituwa a cikin buƙatun iri ɗaya.
Za a iya fallasa bayanan rubutu mai ma'ana idan ikon samun dama yana da rauni.
Taswirar Hanya
Ƙayyade tsarin fitarwa, sautin, da ma'auni masu inganci kafin fitowa.
Ƙayyade tsarin fitarwa, sautin, da ma'auni masu inganci kafin fitowa. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Amsa a ƙasa tare da amintattun tushe a duk lokacin da daidaito ya shafi mahimmanci.
Amsa a ƙasa tare da amintattun tushe a duk lokacin da daidaito ya shafi mahimmanci. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Ajiye wurin binciken ɗan adam don abubuwan da ake samu masu girma.
Ajiye wurin binciken ɗan adam don abubuwan da ake samu masu girma. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Bibiyar tsarin gazawar kuma sake horar da tsokaci ko tafiyar aiki akai-akai.
Bibiyar tsarin gazawar kuma sake horar da tsokaci ko tafiyar aiki akai-akai. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.