Jagorar Fasaha

1-Bit da Ternary BitNet Model

BitNet shine layin bincike na Microsoft yana nuna cewa ana iya horar da manyan nau'ikan harshe tare da iyakance ma'auni zuwa kawai 1 bit, ko ƙima uku a cikin harka ta ternary.

Dubawa

BitNet shine layin bincike na Microsoft yana nuna cewa ana iya horar da manyan nau'ikan harshe tare da iyakance ma'auni zuwa kawai 1 bit, ko ƙima uku a cikin harka ta ternary. Wannan yana rage ƙwaƙwalwar ajiya da amfani da kuzari sosai yayin kiyaye daidaito mai ƙarfi mai ban mamaki.

1-Bit da Ternary BitNet Models wani shingen ginin fasaha ne wanda ke shafar ingancin samfurin, farashin kayan aiki, latency, da aminci a sikelin.

Zurfafa nutsewa

Samfuran al'ada suna adana kowane nauyi azaman lamba 16-bit. BitNet ya maye gurbin waɗannan tare da matsananci ƙananan wakilci. Bambancin BitNet b1.58 mai tasiri yana amfani da ma'auni na uku, kowanne an iyakance shi zuwa -1, 0, ko +1, wanda ke aiki zuwa kusan 1.58 rago na bayanai akan kowane nauyi (log tushe 2 na 3). Muhimmin ra'ayi shine cewa ƙirar an horar da ita daga karce tare da waɗannan ƙuntatawa, ba a ƙididdige su daga baya ba, don haka ya koyi zama mai ƙarfi zuwa ƙayyadaddun daidaito. Saboda ma'auni ne kawai -1, 0, ko +1, tsada mai yawa a cikin matrix math yana rushewa zuwa ƙari da raguwa. Sakamakon yana da nisa ƙananan bandwidth na ƙwaƙwalwar ajiya, amfani da makamashi, da latency, tare da ƙimar 0 kuma yana ba da damar ɓarna, duk yayin da ya dace da ingantattun samfura a girman kwatankwacin kan ma'auni da yawa.

Fahimtar Fasaha

BitNet yana amfani da Layer BitLinear na al'ada wanda ke ƙididdige ma'auni zuwa na uku da kunnawa zuwa ƙananan daidaito yayin wucewar gaba, yayin da yake kiyaye kwafin 'inuwa' mafi girma na ma'aunin nauyi don sabuntawar gradient ta hanyar ƙididdigewa kai tsaye. Saboda kowane nauyi shine -1, 0, ko +1, samfuran ɗigo waɗanda ke mamaye lissafin taswira sun zama ƙari da ragi maimakon ninka-maki-ruwa, wanda shine ke buɗe ƙarfin kuzari da ribar sauri akan kayan aikin da suka dace.

Kwarewar 1-Bit da Tsarin BitNet na Ternary

BitNet shine layin bincike na Microsoft yana nuna cewa ana iya horar da manyan nau'ikan harshe tare da iyakance ma'auni zuwa kawai 1 bit, ko ƙima uku a cikin harka ta ternary. Wannan yana rage ƙwaƙwalwar ajiya da amfani da kuzari sosai yayin kiyaye daidaito mai ƙarfi mai ban mamaki. 1-Bit da Ternary BitNet Models wani shingen ginin fasaha ne wanda ke shafar ingancin samfurin, farashin kayan aiki, latency, da aminci a sikelin. Don gina zurfin fahimta, bi da 1-Bit da Ternary BitNet Model a matsayin samfurin aiki, ba sifa ɗaya ba: ayyana sakamakon da ake so, bayyana zato, da kuma 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 masu amfani da 1-Bit da Ternary BitNet Model suna haɓaka gine-gine, bayanai, da zaɓin abubuwan more rayuwa akan dogaro da farashi. 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.

Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. A lokaci guda, Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin. 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

Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru.

Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. 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.

Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba.

Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu 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.

Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa.

Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa. 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.

Makomar 1-Bit da Tsarin BitNet na Ternary

BitNet yana nuni zuwa gaba inda samfura masu ƙarfi ke gudana akan wayoyi, kwamfyutocin kwamfyutoci, da na'urorin gefen ba tare da GPUs na datacenter ba. Babban ƙwanƙwasa kayan aiki ne: kwakwalwan kwamfuta na yau an gina su ne don lissafi mai iyo, don haka ƙwararrun masu haɓakawa waɗanda aka inganta don ƙarin ayyuka na ternary-kawai na iya haɓaka fa'idodin. Yi tsammanin ƙarin ƙirar gine-ginen 1-bit na ƙasa, samfuran tsarin BitNet mafi girma, da haɗin kai cikin mataimakan na'urori inda rayuwar baturi da keɓantawa, mai yuwuwar sake fasalin tattalin arziƙin AI.

Aiwatar da Gaskiyar Duniya

Microsoft's BitNet b1.58 2B4T yana gudana yadda ya kamata akan CPU, yana ba da damar tantance LLM ba tare da keɓaɓɓen GPU ba.

Mataimakan kan na'ura waɗanda suka dace da ƙirar ƙira cikin ƙayyadaddun ƙwaƙwalwar ajiyar waya godiya ga ma'aunin ~1.58-bit.

Rage ƙimar ƙima da ƙimar carbon don sabis na API mai girma ta hanyar maye gurbin abubuwan da ke iyo ninkawa tare da ƙari.

Aiwatar da Edge (IoT, kayan aikin da aka haɗa) inda ma'aunin nauyi ya sa fahimtar harshen gida ya yiwu a cikin matsananciyar kasafin kuɗi.

Hanyoyin Aiwatarwa

1-Bit da Ternary BitNet Model a aikace

Microsoft's BitNet b1.58 2B4T yana gudana yadda ya kamata akan CPU, yana ba da damar tantance LLM ba tare da keɓaɓɓen GPU ba.

Microsoft's BitNet b1.58 2B4T yana gudana yadda ya kamata akan CPU, yana ba da damar ƙaddamar da LLM ba tare da Ƙungiyoyin GPU da aka keɓe ba yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararraki, da bin diddigin nasarorin samarwa da ƙimar kuskure akan lokaci.

1-Bit da Ternary BitNet Model a aikace

Mataimakan kan na'ura waɗanda suka dace da ƙirar ƙira cikin ƙayyadaddun ƙwaƙwalwar ajiyar waya godiya ga ma'aunin ~1.58-bit.

Mataimakan na'ura waɗanda suka dace da ƙirar ƙira cikin ƙayyadaddun ƙwaƙwalwar ajiyar waya godiya ga ~ 1.58-bit ma'aunan Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararraki, da bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.

1-Bit da Ternary BitNet Model a aikace

Rage ƙimar ƙima da ƙimar carbon don sabis na API mai girma ta hanyar maye gurbin abubuwan da ke iyo ninkawa tare da ƙari.

Rage yawan kuzarin ƙima da farashin carbon don sabis na API mai girma ta hanyar maye gurbin ninka-maki-ruwa tare da tarawa 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 kuma bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.

1-Bit da Ternary BitNet Model a aikace

Aiwatar da Edge (IoT, kayan aikin da aka haɗa) inda ma'aunin nauyi ya sa fahimtar harshen gida ya yiwu a cikin matsananciyar kasafin kuɗi.

Aiwatar da Edge (IoT, kayan aikin da aka haɗa) inda ma'aunin nauyi ya sa fahimtar harshen gida ya zama mai yuwuwa a cikin matsananciyar kasafin kuɗi Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓaka ɗan adam don ƙararraki, da bin diddigin nasarorin samarwa da tsadar kurakurai akan lokaci.

Hatsari & Tsare-tsare

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Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin.

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Sau da yawa ana raina kayan more rayuwa da kuma kuɗin kulawa.

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Tsaro da gibin lura na iya girma yayin da tsarin ke ƙara haɓaka.

Taswirar Hanya

1

Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa.

Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.

2

Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai.

Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.

3

Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani.

Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.

4

Shirya bijirowa da hanyoyin mayar da martani kafin sikeli.

Shirya bijirowa da hanyoyin mayar da martani kafin sikeli. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.

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