Dubawa
BentoML shine tsarin Python mai buɗewa wanda ke haɗa samfuran injunan koyan injuna zuwa daidaitattun raka'a, da za a iya turawa da ake kira 'Bentos'. Yana cike gibin da ke tsakanin samfurin da ke zaune a cikin littafin rubutu da sabis na samarwa wanda zai iya ba da tsinkaya a zahiri akan API.
BentoML da Model Packaging wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli.
Zurfafa nutsewa
Lokacin da masanin kimiyyar bayanai ya gama horar da ƙira, shigar dashi cikin samarwa yawanci yana nufin rubuta lambar sabis da hannu, haɗa abubuwan dogaro, gina hoton Docker, da haɗa API. BentoML yana sarrafa wannan. Kuna ajiye samfuri zuwa kantin sayar da samfurin gida, sannan ku ayyana ajin Sabis tare da ƙarshen API wanda aka ƙawata don sarrafa tunani. Umurnin 'bentoml gini' ya ƙunshi samfurin, lambar Python ku, nau'ikan dogaro, da daidaitawar lokacin aiki zuwa cikin abin da ya ƙunshi kansa, sigar Bento. Daga can 'bentoml containerize' yana samar da hoton OCI Docker. BentoML yana goyan bayan kusan kowane tsarin (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers, ONNX) kuma yana ƙara ƙaramar ƙaramar batching, waɗanda ke haɗa buƙatun masu shigowa ta atomatik don haɓaka kayan aikin GPU ba tare da canza lambar ku ba.
Fahimtar Fasaha
BentoML yana raba 'Masu gudu' (kisa-ƙirar ƙirar ƙira) daga dabarar uwar garken API. Masu gudu za su iya yin sikelin kansu da kansu kuma suna gudanar da ayyukan ma'aikatansu, yayin da uwar garken HTTP/gRPC mai nauyi ke sarrafa buƙatun routing da I/O. Batching ɗin sa na daidaitawa yana jujjuya girman juzu'i da taga latency a lokacin aiki, don haka yana ɗaukar fashewar zirga-zirgar ababen hawa kuma yana sa masu saurin gudu masu tsada. Madaidaicin tsarin Bento yana ƙunshe da bayyanuwa, fayilolin ƙira, da mahalli da za'a iya sakewa, yana gina ƙayyadaddun ƙayyadaddun injuna.
Mastering BentoML da Model Packaging
BentoML shine tsarin Python mai buɗewa wanda ke haɗa samfuran injunan koyan injuna zuwa daidaitattun raka'a, da za a iya turawa da ake kira 'Bentos'. Yana cike gibin da ke tsakanin samfurin da ke zaune a cikin littafin rubutu da sabis na samarwa wanda zai iya ba da tsinkaya a zahiri akan API. BentoML da Model Packaging wani shingen gini ne na fasaha wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli. Don gina zurfin fahimta, bi da BentoML da Model Packaging a matsayin samfurin aiki, ba sifa ɗaya ba: ayyana sakamakon da ake so, fayyace zato, 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 BentoML da Model Packaging 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.
Aiwatar da Gaskiyar Duniya
Ƙungiyar gano zamba tana adana samfurin XGBoost zuwa kantin BentoML kuma ta gina Bento wanda ke fallasa ƙarshen ƙarshen REST don sabis na biyan kuɗi don kira a ainihin lokacin.
Ƙungiyar dandalin ML tana amfani da 'bentoml containerize' don juya samfurin Hugging Fuska zuwa hoton Docker wanda ke tura gungu na Kubernetes na ciki.
Farawa yana ba da ingantaccen tsarin Llama mai kyau tare da OpenLLM (wanda aka gina akan BentoML), alamun yawo zuwa UI taɗi tare da daidaita daidaitawar GPU.
Wani kamfani mai hangen nesa na kwamfuta yana haɗa nau'in nau'in hoto na PyTorch tare da sarrafa bututunsa zuwa Bento ɗaya don haka ainihin sauye-sauyen da aka yi amfani da su wajen horar da jirgin ruwa tare da samfurin.
Hanyoyin Aiwatarwa
BentoML da Model Packaging a aikace
Ƙungiyar gano zamba tana adana samfurin XGBoost zuwa kantin BentoML kuma ta gina Bento wanda ke fallasa ƙarshen ƙarshen REST don sabis na biyan kuɗi don kira a ainihin lokacin.
Ƙungiyar gano zamba tana adana samfurin XGBoost zuwa kantin sayar da BentoML kuma ta gina Bento wanda ke fallasa ƙarshen ƙarshen sabis na biyan kuɗi don kira a cikin ainihin lokacin 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 diddigin abubuwan samarwa da ƙimar kuskure akan lokaci.
BentoML da Model Packaging a aikace
Ƙungiyar dandalin ML tana amfani da 'bentoml containerize' don juya samfurin Hugging Fuska zuwa hoton Docker wanda ke tura gungu na Kubernetes na ciki.
Ƙungiyar dandamali ta ML tana amfani da 'bentoml containerize' don juya samfurin Hugging Fuskar zuwa hoton Docker wanda ke tura zuwa ƙungiyoyin gungu na Kubernetes na ciki 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 farashi na kuskure akan lokaci.
BentoML da Model Packaging a aikace
Farawa yana ba da ingantaccen tsarin Llama mai kyau tare da OpenLLM (wanda aka gina akan BentoML), alamun yawo zuwa UI taɗi tare da daidaita daidaitawar GPU.
Farawa yana ba da kyakkyawan tsarin Llama mai kyau tare da OpenLLM (wanda aka gina akan BentoML), alamun yawo zuwa UI taɗi tare da daidaita daidaitawar ƙungiyoyin GPU 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 abubuwan samarwa da ƙimar kuskure akan lokaci.
BentoML da Model Packaging a aikace
Wani kamfani mai hangen nesa na kwamfuta yana haɗa nau'in nau'in hoto na PyTorch tare da sarrafa bututunsa zuwa Bento ɗaya don haka ainihin sauye-sauyen da aka yi amfani da su wajen horar da jirgin ruwa tare da samfurin.
Kamfanin hangen nesa na kwamfuta yana haɗa nau'in hoton hoto na PyTorch tare da bututun da ya riga ya tsara zuwa cikin Bento don haka ainihin sauye-sauyen da aka yi amfani da su a cikin jirgin horo tare da ƙirar 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 kuma bin diddigin nasarorin samarwa da ƙimar kuskure a kan lokaci.
Hatsari & Tsare-tsare
Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin.
Sau da yawa ana raina kayan more rayuwa da kuma kuɗin kulawa.
Tsaro da gibin lura na iya girma yayin da tsarin ke ƙara haɓaka.
Taswirar Hanya
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.
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.
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.
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.