{"id":106018,"date":"2022-12-13T09:36:49","date_gmt":"2022-12-13T07:36:49","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-sistemy-mashinnogo-perevoda-opennmt-tf-2-30"},"modified":"2022-12-13T09:36:49","modified_gmt":"2022-12-13T07:36:49","slug":"vypusk-sistemy-mashinnogo-perevoda-opennmt-tf-2-30","status":"publish","type":"post","link":"https:\/\/prohoster.info\/ro\/blog\/news\/vypusk-sistemy-mashinnogo-perevoda-opennmt-tf-2-30","title":{"rendered":"Lansarea sistemului de traducere automat\u0103 OpenNMT-tf 2.30","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>A fost lansat\u0103 versiunea sistemului de traducere automat\u0103 OpenNMT-tf 2.30.0 (Open Neural Machine Translation), care utilizeaz\u0103 metode de \u00eenv\u0103\u021bare automat\u0103. Codul modulelor dezvoltate de proiectul OpenNMT-tf este scris \u00een Python, folose\u0219te biblioteca TensorFlow \u0219i este distribuit sub licen\u021ba MIT.     <\/p>\n<p>\u00cen paralel, se dezvolt\u0103 o variant\u0103 OpenNMT bazat\u0103 pe biblioteca PyTorch, care difer\u0103 \u00een ceea ce prive\u0219te func\u021bionalit\u0103\u021bile suportate. \u00cen plus, OpenNMT bazat\u0103 pe PyTorch este prezentat\u0103 ca fiind mai u\u0219or de utilizat \u0219i multimodal\u0103, \u00een timp ce varianta bazat\u0103 pe TensorFlow este remarcat\u0103 ca fiind modular\u0103, stabil\u0103 \u0219i capabil\u0103 s\u0103 utilizeze capacit\u0103\u021bile GPU pentru accelerarea procesului de \u00eenv\u0103\u021bare a re\u021belei neuronale. Pentru a simplifica distribu\u021bia produsului, proiectul dezvolt\u0103, de asemenea, o variant\u0103 autonom\u0103 a traduc\u0103torului \u00een limbajul C++ \u2014 CTranslate2, care folose\u0219te modele pre-antrenate f\u0103r\u0103 leg\u0103tura cu dependen\u021be suplimentare.         <\/p>\n<p>Modelele sunt preg\u0103tite pentru limbile englez\u0103, german\u0103 \u0219i catalan\u0103; pentru celelalte limbi, se poate crea propria model pe baza setului de date de la proiectul OPUS (pentru a antrena sistemul se transmit dou\u0103 fi\u0219iere \u2014 unul cu propozi\u021bii \u00een limba surs\u0103 \u0219i cel\u0103lalt cu traducerea de calitate a acestor propozi\u021bii \u00een limba \u021bint\u0103).    <\/p>\n<p>Proiectul se dezvolt\u0103 cu contribu\u021bia companiei SYSTRAN, specializat\u0103 \u00een crearea instrumentelor de traducere automat\u0103, \u0219i a unui grup de cercet\u0103tori de la Harvard, care dezvolt\u0103 modele de limbaj uman pentru sistemele de \u00eenv\u0103\u021bare automat\u0103. Interfa\u021ba utilizatorului este maxim simplificat\u0103 \u0219i necesit\u0103 doar indicarea fi\u0219ierului de intrare cu textul \u0219i a fi\u0219ierului pentru salvarea rezultatului traducerii. Sistemul de extensii permite realizarea de func\u021bionalit\u0103\u021bi suplimentare pe baza OpenNMT, cum ar fi autoreferin\u021bierea, clasificarea textelor \u0219i generarea de subtitr\u0103ri.     <\/p>\n<p>\u00cen noua versiune:  <\/p>\n<ul>\n<li class=\"l\"> A fost ad\u0103ugat\u0103 suportul pentru biblioteca TensorFlow 2.11, dar noii optimizatori Keras nu sunt \u00eenc\u0103 suporta\u021bi (este necesar\u0103 utilizarea modului tf.keras.optimizers.legacy).\n<li class=\"l\"> A fost ad\u0103ugat\u0103 suportul pentru noua ramur\u0103 a motorului CTranslate2 3.x, destinat execut\u0103rii eficiente a modelelor cu arhitectur\u0103 \u201etransformer\u201d.\n<li class=\"l\"> A fost ad\u0103ugat parametrul de antrenare a modelelor pad_to_bucket_boundary pentru a include umplutura suplimentar\u0103, care aliniaz\u0103 dimensiunea blocului la valori care sunt m\u00faltipli de length_bucket_width.\n<li class=\"l\"> A fost integrat suportul pentru metricile chrf \u0219i chrf++ din proiectul SacreBLEU, care compar\u0103 traducerea automat\u0103 cu traducerea uman\u0103 de referin\u021b\u0103.\n<li class=\"l\"> A fost eliminat atributul modelului ctranslate2_spec, care nu mai este utilizat \u00een CTranslate2.  <\/ul>\n<p>Sursa: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=58316\">opennet.ro<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d \u0432\u044b\u043f\u0443\u0441\u043a \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043f\u0435\u0440\u0435\u0432\u043e\u0434\u0430 OpenNMT-tf 2.30.0 (Open Neural Machine Translation), \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0449\u0435\u0439 \u043c\u0435\u0442\u043e\u0434\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u041a\u043e\u0434 \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u043c\u044b\u0445 \u043f\u0440\u043e\u0435\u043a\u0442\u043e\u043c OpenNMT-tf \u043c\u043e\u0434\u0443\u043b\u0435\u0439 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Python, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0443 TensorFlow \u0438 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u0435\u0439 MIT. \u041f\u0430\u0440\u0430\u043b\u043b\u0435\u043b\u044c\u043d\u043e \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u0442\u0441\u044f \u0432\u0430\u0440\u0438\u0430\u043d\u0442 OpenNMT \u043d\u0430 \u0431\u0430\u0437\u0435 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 PyTorch, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043e\u0442\u043b\u0438\u0447\u0430\u0435\u0442\u0441\u044f \u043d\u0430 \u0443\u0440\u043e\u0432\u043d\u0435 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0435\u043c\u044b\u0445 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u0435\u0439. \u041a\u0440\u043e\u043c\u0435 \u0442\u043e\u0433\u043e, OpenNMT \u043d\u0430 \u0431\u0430\u0437\u0435 PyTorch \u043f\u0440\u0435\u043f\u043e\u0434\u043d\u043e\u0441\u0438\u0442\u0441\u044f \u043a\u0430\u043a \u0431\u043e\u043b\u0435\u0435 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-106018","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2.1 - aioseo.com -->\n\t<meta name=\"description\" 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