BentoML ak xeetu emballage
BentoML benn kaadaru Python la bu ubbeeku, muy boole ay xeeti jàngu masin yuñ tàggat ci ay yunit yuñ mëna jëfandikoo, ñu tuddee ko 'Bentos'.
Résumé
Dafay dindi bërëb bi nekk ci digganté ab model bu toog ci benn kaye ak ab sarwiisu defar bu mëna def ay wax luy waaja am ci benn API.
Plongeur bu xóot
Su gëstukat bi jeexalee ci tàggat benn model, dugal ko ci liggéey dafay faral di tekki bind kodu serwiis ak loxo, pinning dependency, tabax nataalu Docker, ak wiring API. BentoML dafay otomatise lii. Yaa ngi denc benn model ci magasin model bi ci dëkk bi, ba noppi nga joxe benn klaasu Serwiis bu am poñ API buñ defar ngir mëna jëfandikoo inference. Komànd 'bentoml build' dafay boole model bi, sa kodu Python, xeetu dependence yi, ak tabb runtime ci benn Bento bu nekk ci boppam, buñ joxe xeetu Bento. Foofu 'bentoml conteneriser' defar nataalu OCI Docker. BentoML dafay jàppale daanaka bépp kaadar (PyTorch, TensorFlow, scikit-jàng, XGBoost, Transformatëri kanam yuy laxasu, ONNX) ba noppi yokk ay micro-batching yuy méngoo, yuy boole laaj yiy dugg ci saasi ngir yokk GPU bi te doo soppi sa kode.
Gis-gis xarala
BentoML dafay tàqale 'Runners' (xeetu jëfandikoo model bu diis) ak logiku serwëru API. Runners mën nañu scale seen bopp ba noppi daw ci seeni processus liggéeykat, ci noonu la serveur HTTP/gRPC bu woyof bi di yoree routing ak I/O. Batching bimu àndal dafay méngale dayo batch bi ak palanteer bu latency bi ci runtime bi, suko defee mu mëna xëcci trafik bi ba noppi di tëye accelerator yu seer yi. Format Bento biñ yamale dafay boole ay manifest, ay fichier model, ak environmaa buñ mëna defaraat, loolu mooy tax defar yi nekk ci masin yi.
njeextalu pexe
Njëgg ak budget
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw.
dogal yu gëna leer
Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal.
Xool kalite
Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi.
Ëlëgu BentoML ak xeetu emballage
BentoML dafa wéeru bu baax ci xeetu làkk bu yaatu ak sarwiisu IA buy defar, OpenLLM ak BentoCloud di joxe tontu ci token, autoscaling, ak xam-xam GPU. Xaarandi lëkkaloo bu gëna dëgër ak optimisatër yu melni vLLM ak TensorRT-LLM, jàppale bu gëna baax ci sistem IA yu bari, ak yoon yu gëna neexa joge ci Bento buñ defar ba ci GPU bu amul serwër. Bi ekip yi jogee ci benn model dem ci pipeline agent, BentoML mingi taxawal boppam ni couche de emballage ak de service biy boole composant yooyu.
Doxal ci àdduna dëgg
Ekipu gis-gis njuuj njaaj dafay denc benn xeetu XGBoost ci bitik BentoML ba noppi tabax benn Bento buy wane / predict REST endpoint ngir serwiisu fayukaay yi woo ci jamono dëgg.
Benn ekipu platform ML dafay jëfandikoo 'bentoml contenerize' ngir soppi xeetu yëg-yëgu kanam buy laxasu ci nataalu Docker buy dugal ci seen cluster Kubernetes bi ci biir.
Benn startup dafay liggéey ci xeetu Llama buñ defar bu baax ak OpenLLM (ñu tabax ci kaw BentoML), di joxe ay token ci interfaasu jëfandikukat buy waxtaan ak batching buy méngoo ak GPU bi.
Benn kompiñi buy xool ci ordinatër dafay boole benn xeetu nataalu PyTorch ak gasoduk preprocessing bi ci benn Bento suko defee ñu mëna soppi gaal gi gëna jubal ci tàggat gaal gi ak model bi.
Risk yi ak balustrade yi
Optimize benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi.
Njëg li ñuy fay ci infrastructure yi ak ci toppatoo dañuy faral di suufeel.
Bu sistem yi di gëna xawa jafee xam, jafe-jafe yi am ci wàllu kaaraange ak seetlu mën nañu gëna bari.
Roadmap ngir samp gi
Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo.
Benchmark ci biir sargal ak done yu dëggu.
Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi.
Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale.
Weyal di banneexu
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Laaj yi ñuy faral di laaj
Luy BentoML ak xeetu emballage?
BentoML benn kaadaru Python la bu ubbeeku, muy boole ay xeeti jàngu masin yuñ tàggat ci ay yunit yuñ mëna jëfandikoo, ñu tuddee ko 'Bentos'. Dafay dindi bërëb bi nekk ci digganté ab model bu toog ci benn kaye ak ab sarwiisu defar bu mëna def ay wax luy waaja am ci benn API.
Lan mooy jumtukaay biñ mëna jëfandikoo, bi BentoML di defar?
BentoML dafay boole ab model, kodam, ay dependansi, ak config runtime ci benn jumtukaay buñ soppali, bu nekk ci boppam bu tuddu Bento.
Lan mooy gëna suqaliku ci micro-batching bu BentoML?
Batching biy méngoo dafay boole ay laaj yuy dugg ci runtime ngir GPU yi nekk ci liggéey ba noppi yokk produit yi te duñu soppi kode bi.
Ci architecture BentoML, lan mooy yoriinu jëfandikoo model bu diis bi te wuute ak serwëru API bi?
Runners yi dañuy encapsuler model inference te mën nañu scale ci seeni processus liggéeykat, ñu jële ko ci serwëru API bu woyof bi.
Ban komand mooy soppi Bento biñ tabax ci nataalu OCI Docker?
'bentoml conteneriser' dafay defar nataalu OCI/Docker buñ miin bu bawoo ci Bento ngir génne ko.
Ci yii, ban ci ñoom moo waral BentoML di samp ay xeetu dependence ci Bento?
Pinning ak embedding environmaa bi dafay tax serwiis biñ defar mën nañu ko defaraat ba noppi di méngoo fépp fuñu ko mëna defee.