{"id":234047,"date":"2024-04-04T05:30:00","date_gmt":"2024-04-04T05:30:00","guid":{"rendered":"https:\/\/datascientest.com\/?p=234047"},"modified":"2024-04-18T14:18:44","modified_gmt":"2024-04-18T14:18:44","slug":"llmops-tout-savoir","status":"publish","type":"post","link":"https:\/\/datascientest.com\/llmops-tout-savoir","title":{"rendered":"LLMOps ou comment g\u00e9rer les grands mod\u00e8les de langage"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"234047\" class=\"elementor elementor-234047\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-20a332b e-flex e-con-boxed e-con\" data-id=\"20a332b\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5a2a3d9 elementor-widget elementor-widget-heading\" data-id=\"5a2a3d9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Depuis le d\u00e9ploiement de ChatGPT, Bard ou autres mod\u00e8les de LLM, de plus en plus d\u2019entreprises utilisent, con\u00e7oivent et d\u00e9ploient de grands mod\u00e8les de langage. D\u2019o\u00f9 la n\u00e9cessit\u00e9 d\u2019optimiser la gestion op\u00e9rationnelle. C\u2019est l\u00e0 qu\u2019intervient le LLMOps. Alors de quoi s\u2019agit-il ?<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-30b28d9 e-flex e-con-boxed e-con\" data-id=\"30b28d9\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a7480a8 elementor-widget elementor-widget-heading\" data-id=\"a7480a8\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Qu\u2019est-ce que LLMOps ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cf3ff11 elementor-widget elementor-widget-text-editor\" data-id=\"cf3ff11\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><span style=\"font-weight: 400;\">LLMOps est l\u2019anagramme pour <i>\u00ab\u00a0op\u00e9rations de grands mod\u00e8les de langage\u00a0\u00bb<\/i>. Elles englobent toutes les pratiques, techniques et outils utilis\u00e9s pour la<\/span><b> gestion op\u00e9rationnelle des larges languages models<\/b><span style=\"font-weight: 400;\"> dans des environnements de production.<\/span><\/p><p><span style=\"font-weight: 400;\">L\u2019objectif du LLMOps est alors d&rsquo;optimiser le d\u00e9ploiement, la surveillance et la maintenance des <a href=\"https:\/\/datascientest.com\/large-language-models-tout-savoir\">grands mod\u00e8les de langage<\/a>.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4d2f636 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"4d2f636\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"#elementor-action%3Aaction%3Dpopup%3Aopen%26settings%3DeyJpZCI6IjIzODI2MiIsInRvZ2dsZSI6ZmFsc2V9\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Se former au LLMOps<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6c0d79e elementor-widget elementor-widget-heading\" data-id=\"6c0d79e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">L\u2019importance du LLMOps<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-650ef15 elementor-widget elementor-widget-text-editor\" data-id=\"650ef15\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Pour rappel, les LLM constituent une avanc\u00e9e par rapport aux mod\u00e8les traditionnels de <a href=\"https:\/\/datascientest.com\/introduction-au-nlp-natural-language-processing\">traitement du langage naturel (NLP)<\/a>. Et pour cause, ils sont <\/span><b>capables de r\u00e9aliser des t\u00e2ches extr\u00eamement complexes<\/b><span style=\"font-weight: 400;\"> ; depuis la r\u00e9ponse \u00e0 des questions ouvertes jusqu&rsquo;\u00e0 la synth\u00e8se en passant par le suivi d&rsquo;instructions quasi-arbitraires. \u00c0 mesure que les avanc\u00e9es technologiques \u00e9voluent, les LLM int\u00e8grent de plus en plus les comportements humains. Mais ces avanc\u00e9es impliquent encore de<\/span><b> nombreux d\u00e9fis<\/b><span style=\"font-weight: 400;\">. Et ce, \u00e0 plusieurs niveaux :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">La collecte de donn\u00e9es ;\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">La pr\u00e9paration des donn\u00e9es ;<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">La collaboration entre les \u00e9quipes de <a href=\"https:\/\/datascientest.com\/la-data-science-prend-dassaut-le-marche-de-limmobilier\">data science<\/a>, data engineering\u2026 ;\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">L&rsquo;ing\u00e9nierie des prompts ;\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Le r\u00e9glage fin du mod\u00e8le (<a href=\"https:\/\/datascientest.com\/fine-tuning-tout-savoir\">fine tuning<\/a>) ;<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Le d\u00e9ploiement du mod\u00e8le ;\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">La surveillance du mod\u00e8le ; <\/span><\/li><li aria-level=\"1\"><span style=\"font-weight: 400;\">Etc.<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dfa5698 elementor-widget elementor-widget-text-editor\" data-id=\"dfa5698\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">De par tous ces d\u00e9fis \u00e0 relever, il est primordial d<\/span><b>\u2019impl\u00e9menter une rigueur op\u00e9rationnelle pour synchroniser l\u2019ensemble des processus.<\/b><span style=\"font-weight: 400;\"> C\u2019est justement le r\u00f4le du LLMOp.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d881972 elementor-widget elementor-widget-image\" data-id=\"d881972\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"875\" height=\"500\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps1.jpg\" class=\"attachment-full size-full wp-image-234066\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps1.jpg 875w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps1-300x171.jpg 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps1-768x439.jpg 768w\" sizes=\"(max-width: 875px) 100vw, 875px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d298125 elementor-widget elementor-widget-heading\" data-id=\"d298125\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">LLMOps vs MLOps<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c5dca2a elementor-widget elementor-widget-text-editor\" data-id=\"c5dca2a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Corollaire du LLMOps, il y a le MLOps (pour les op\u00e9rations <a href=\"https:\/\/datascientest.com\/machine-learning-tout-savoir\">en mati\u00e8re de machine learning<\/a>). Bien que compl\u00e9mentaires, ces deux techniques m\u00e9ritent d\u2019\u00eatre distingu\u00e9es :\u00a0<\/span><\/p><ul><li><b>Les ressources informatiques <\/b><span style=\"font-weight: 400;\">: de par la performance des larges languages models, ces derniers n\u00e9cessitent des ressources suppl\u00e9mentaires (comme les <a href=\"https:\/\/datascientest.com\/gpu-data-science\">GPU<\/a>) avec des ordres de grandeur plus fins.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>L\u2019apprentissage par transfert <\/b><span style=\"font-weight: 400;\">: les mod\u00e8les de ML traditionnels sont g\u00e9n\u00e9ralement cr\u00e9\u00e9s \u00e0 partir de z\u00e9ro. Ce n\u2019est pas le cas des grands mod\u00e8les de langage qui partent d&rsquo;un mod\u00e8le de base. Ils sont affin\u00e9s avec de nouvelles donn\u00e9es pour offrir aux utilisateurs des performances de haut niveau.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Le retour d&rsquo;information humain :<\/b><span style=\"font-weight: 400;\"> pour affiner leurs performances, les LLM fonctionnent majoritairement \u00e0 partir de l&rsquo;apprentissage par renforcement \u00e0 partir du retour d&rsquo;information humain (RLHF). L&rsquo;int\u00e9gration de cette boucle dans les pipelines LLMOps facilite l&rsquo;ajustement des grands mod\u00e8les de langage.\u00a0<\/span><\/li><li><b>Le r\u00e9glage des hyperparam\u00e8tres :<\/b><span style=\"font-weight: 400;\"> en machine learning, le r\u00e9glage se focalise sur l&rsquo;am\u00e9lioration de la pr\u00e9cision ou d&rsquo;autres mesures. \u00c0 l\u2019inverse, pour les LLM, le <a href=\"https:\/\/datascientest.com\/hyperparametres-tout-savoir\">r\u00e9glage des hyperparam\u00e8tres<\/a> permet souvent de r\u00e9duire le co\u00fbt et la puissance de calcul n\u00e9cessaires \u00e0 la formation et \u00e0 l&rsquo;inf\u00e9rence.<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ba0927c elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"ba0927c\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"#elementor-action%3Aaction%3Dpopup%3Aopen%26settings%3DeyJpZCI6IjIzODI2MiIsInRvZ2dsZSI6ZmFsc2V9\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">D\u00e9couvrir le LLMOps<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d6135be e-flex e-con-boxed e-con\" data-id=\"d6135be\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-8d4da2a elementor-widget elementor-widget-heading\" data-id=\"8d4da2a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Quelles sont les bonnes pratiques LLMOps ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d12fdd3 elementor-widget elementor-widget-text-editor\" data-id=\"d12fdd3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Vous l\u2019aurez compris, le LLMOps d\u00e9finit un ensemble de bonnes pratiques op\u00e9rationnelles pour optimiser la gestion des grands mod\u00e8les de langage. Mais quelles sont ces pratiques ? En r\u00e9alit\u00e9, il y en a plusieurs selon l\u2019\u00e9tape du LLM :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>L\u2019analyse exploratoire des donn\u00e9es (AED)<\/b><span style=\"font-weight: 400;\"> : l\u2019exploration des donn\u00e9es disponibles est indispensable, puisque chaque information servira \u00e0 l&rsquo;<a href=\"https:\/\/datascientest.com\/apprentissage-automatique\">apprentissage automatique<\/a>.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>La pr\u00e9paration des donn\u00e9es<\/b><span style=\"font-weight: 400;\"> : il s\u2019agit de transformer les donn\u00e9es pour les rendre visibles et accessibles aux \u00e9quipes charg\u00e9es de d\u00e9ployer les LLM. Pour cela, il convient de concevoir des tableaux, des visualisations reproductibles, modifiables et partageables.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>L\u2019ajustement du mod\u00e8le<\/b><span style=\"font-weight: 400;\"> : pour affiner les performances des mod\u00e8les, il est possible d\u2019utiliser plusieurs biblioth\u00e8ques open source comme <a href=\"https:\/\/datascientest.com\/hugging-face-transformers-tout-savoir\">Hugging Face Transformers<\/a>, DeepSpeed, <a href=\"https:\/\/datascientest.com\/pytorch-tout-savoir\">PyTorch<\/a>, <a href=\"https:\/\/datascientest.com\/tensorflow\">TensorFlow<\/a>\u2026\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>La r\u00e9vision et gouvernance des mod\u00e8les<\/b><span style=\"font-weight: 400;\"> : LLMOps a vocation \u00e0 optimiser l\u2019ensemble des processus du cycle de vie des grands mod\u00e8les. Vous devez donc suivre l&rsquo;\u00e9volution et les diff\u00e9rentes versions des mod\u00e8les.\u00a0<\/span><\/li><li><b>La surveillance des mod\u00e8les :<\/b><span style=\"font-weight: 400;\"> les pipelines de surveillance \u00e9vitent les hallucinations, les biais ou autres d\u00e9rives. \u00c0 travers des alertes, vous pourrez analyser le comportement des mod\u00e8les. Ici, il est primordial d\u2019impl\u00e9menter une supervision humaine.<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cffc177 elementor-widget elementor-widget-image\" data-id=\"cffc177\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"875\" height=\"500\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps2.jpg\" class=\"attachment-full size-full wp-image-234070\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps2.jpg 875w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps2-300x171.jpg 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/03\/LLMOps2-768x439.jpg 768w\" sizes=\"(max-width: 875px) 100vw, 875px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f1b4fab e-flex e-con-boxed e-con\" data-id=\"f1b4fab\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-73cd174 elementor-widget elementor-widget-heading\" data-id=\"73cd174\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Quels sont les avantages du LLMOps ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-934360f elementor-widget elementor-widget-text-editor\" data-id=\"934360f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">En mettant en place les bonnes pratiques susmentionn\u00e9es, vous pourrez profiter de tous les avantages du LLMOps. \u00c0 savoir :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>L\u2019efficacit\u00e9 :<\/b><span style=\"font-weight: 400;\"> gr\u00e2ce \u00e0 des processus clairs qui ont fait leurs preuves, le LLMOps permet d&rsquo;acc\u00e9l\u00e9rer le d\u00e9veloppement des mod\u00e8les et de fournir des mod\u00e8les de meilleure qualit\u00e9.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>L\u2019\u00e9volutivit\u00e9 :<\/b><span style=\"font-weight: 400;\"> \u00e0 travers une bonne gestion op\u00e9rationnelle des LLM, il est plus facile de g\u00e9rer des milliers de mod\u00e8les.\u00a0<\/span><\/li><li><b>La r\u00e9duction des risques <\/b><span style=\"font-weight: 400;\">: parmi les bonnes pratiques du LLMOps, la surveillance et la supervision sont au centre. Ce qui garantit une plus grande transparence et une r\u00e9ponse plus rapide.<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-54d3149 e-flex e-con-boxed e-con\" data-id=\"54d3149\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-0f409ff elementor-widget elementor-widget-heading\" data-id=\"0f409ff\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Ma\u00eetriser les LLMOps avec DataScientest<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a3c68b4 elementor-widget elementor-widget-text-editor\" data-id=\"a3c68b4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Avec le d\u00e9veloppement des LLM, la gestion op\u00e9rationnelle des grands mod\u00e8les de langage devient l\u2019affaire d\u2019une pluralit\u00e9 d\u2019acteurs. Avec au c\u0153ur, tous les professionnels de l\u2019informatique, tels que les <a href=\"https:\/\/datascientest.com\/salaire-ingenieur-devops\">ing\u00e9nieurs DevOps<\/a>, les <a href=\"https:\/\/datascientest.com\/salaire-data-scientist\">data scientists<\/a>, les <a href=\"https:\/\/datascientest.com\/salaire-data-engineer\">data engineers<\/a>, \u2026 Vous souhaitez adopter les bonnes pratiques et mieux g\u00e9rer les LLM ? <strong>Apprenez l\u2019un de ces m\u00e9tiers avec DataScientest<\/strong>. Sp\u00e9cialis\u00e9s dans la data, nous vous aidons \u00e0 concevoir, d\u00e9ployer et optimiser des mod\u00e8les de langage fiables et performants. <\/span><a href=\"https:\/\/datascientest.com\/formations-data\"><span style=\"font-weight: 400;\">Rejoignez-nous !<\/span><\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8edca6a elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"8edca6a\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"#elementor-action%3Aaction%3Dpopup%3Aopen%26settings%3DeyJpZCI6IjIzODI2MiIsInRvZ2dsZSI6ZmFsc2V9\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Se former au LLMOps<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-105cfec elementor-widget elementor-widget-html\" data-id=\"105cfec\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Qu\u2019est-ce que LLMOps ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"LLMOps est l\u2019anagramme pour \u201cop\u00e9rations de grands mod\u00e8les de langage\u201d. Elles englobent toutes les pratiques, techniques et outils utilis\u00e9s pour la gestion op\u00e9rationnelle des larges languages models dans des environnements de production.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Quels sont les avantages du LLMOps ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"En mettant en place les bonnes pratiques susmentionn\u00e9es, vous pourrez profiter de tous les avantages du LLMOps : l\u2019efficacit\u00e9, l\u2019\u00e9volutivit\u00e9 et la r\u00e9duction des risques.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Pourquoi faut-il ma\u00eetriser le LLMOps ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Avec le d\u00e9veloppement des LLM, la gestion op\u00e9rationnelle des grands mod\u00e8les de langage devient l\u2019affaire d\u2019une pluralit\u00e9 d\u2019acteurs. Avec au c\u0153ur, tous les professionnels de l\u2019informatique, tels que les ing\u00e9nieurs DevOps, les data scientists, les data engineers\u2026\"\r\n    }\r\n  }]\r\n}\r\n<\/script>\r\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Depuis le d\u00e9ploiement de ChatGPT, Bard ou autres mod\u00e8les de LLM, de plus en plus d\u2019entreprises utilisent, con\u00e7oivent et d\u00e9ploient de grands mod\u00e8les de langage. D\u2019o\u00f9 la n\u00e9cessit\u00e9 d\u2019optimiser la gestion op\u00e9rationnelle. C\u2019est l\u00e0 qu\u2019intervient le LLMOps. Alors de quoi s\u2019agit-il ? Qu\u2019est-ce que LLMOps ? LLMOps est l\u2019anagramme pour \u00ab\u00a0op\u00e9rations de grands mod\u00e8les de [&hellip;]<\/p>\n","protected":false},"author":78,"featured_media":234049,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>LLMOps ou comment g\u00e9rer les grands mod\u00e8les de langage<\/title>\n<meta name=\"description\" content=\"Avec l\u2019explosion des grands mod\u00e8les de langage, d\u00e9finir et optimiser une bonne gestion op\u00e9rationnelle s\u2019av\u00e8re indispensable. 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