{"id":18958,"date":"2025-04-23T08:00:15","date_gmt":"2025-04-23T05:00:15","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/"},"modified":"2025-04-23T08:00:15","modified_gmt":"2025-04-23T05:00:15","slug":"docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/","title":{"rendered":"Docker ile Yerel LLM Model \u00c7al\u0131\u015ft\u0131rman\u0131n Basitle\u015ftirilmesi"},"content":{"rendered":"

<\/p>\n

Docker ile Yerel LLM Model \u00c7al\u0131\u015ft\u0131rman\u0131n Basitle\u015ftirilmesi<\/p>\n

B\u00fcy\u00fck dil modelleri (LLM’ler) son y\u0131llarda inan\u0131lmaz bir ilerleme kaydetti. Ancak, bu g\u00fc\u00e7l\u00fc modellerin yerel olarak \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131, genellikle karma\u015f\u0131k ba\u011f\u0131ml\u0131l\u0131klar\u0131 ve yap\u0131land\u0131rma ad\u0131mlar\u0131n\u0131 gerektiren zorlu bir s\u00fcre\u00e7 olabiliyordu. Neyse ki, Docker gibi konteynerle\u015ftirme teknolojileri bu sorunu \u00f6nemli \u00f6l\u00e7\u00fcde hafifletiyor. Bu makalede, Docker’\u0131 kullanarak yerel LLM model y\u00fcr\u00fctmenin nas\u0131l kolayla\u015ft\u0131r\u0131laca\u011f\u0131n\u0131, \u00f6zellikle de Docker Model Runner’\u0131 kullanarak, ayr\u0131nt\u0131l\u0131 olarak ele alaca\u011f\u0131z.<\/p>\n

Docker ve B\u00fcy\u00fck Dil Modelleri: M\u00fckemmel Bir E\u015fle\u015fme<\/h2>\n

\u00d6ncelikle, neden Docker’\u0131n LLM’ler i\u00e7in ideal bir \u00e7\u00f6z\u00fcm oldu\u011funu a\u00e7\u0131klayal\u0131m. Docker, uygulamalar\u0131n\u0131z\u0131 ve ba\u011f\u0131ml\u0131l\u0131klar\u0131n\u0131 bir konteyner i\u00e7inde paketlemenize olanak tan\u0131r. Bu sayede, farkl\u0131 ortamlarda (geli\u015ftirme, test, \u00fcretim) tutarl\u0131 bir \u015fekilde \u00e7al\u0131\u015fmas\u0131n\u0131 sa\u011flar. LLM’ler, genellikle \u00e7e\u015fitli k\u00fct\u00fcphaneler ve \u00f6zel s\u00fcr\u00fcmlere ihtiya\u00e7 duyar. Dolay\u0131s\u0131yla, Docker, bu karma\u015f\u0131k ba\u011f\u0131ml\u0131l\u0131klar\u0131 y\u00f6netmek ve farkl\u0131 sistemler aras\u0131nda sorunsuz bir ge\u00e7i\u015f sa\u011flamak i\u00e7in m\u00fckemmel bir ara\u00e7t\u0131r. Sonu\u00e7 olarak, Docker sayesinde LLM \u00e7al\u0131\u015ft\u0131rmak, daha basit, daha g\u00fcvenilir ve daha ta\u015f\u0131nabilir hale gelir.<\/p>\n

Docker Model Runner: Kurulum ve Kullan\u0131m<\/h2>\n

Docker Model Runner, LLM’lerin Docker konteynerleri i\u00e7inde kolayca \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131n\u0131 sa\u011flayan bir ara\u00e7t\u0131r. Basit bir komutla, modeli indirip, gerekli ba\u011f\u0131ml\u0131l\u0131klar\u0131 kurup, \u00e7al\u0131\u015ft\u0131rmaya haz\u0131r hale getirir. Bu sayede, zahmetli manuel kurulum ve yap\u0131land\u0131rma ad\u0131mlar\u0131ndan kurtulmu\u015f olursunuz. Ayr\u0131ca, farkl\u0131 LLM’leri kolayca de\u011fi\u015ftirerek test edebilirsiniz. \u00d6rne\u011fin, bir modeli \u00e7al\u0131\u015ft\u0131rmak i\u00e7in genellikle \u015fu ad\u0131mlar\u0131 izlersiniz:<\/p>\n

\ndocker run -it -p 8000:8000 \n<\/code><\/pre>\n
Burada, <\/code> yerine, kullanmak istedi\u011finiz LLM modelinin Docker imaj\u0131n\u0131n ad\u0131n\u0131 yazman\u0131z gerekir.  Daha detayl\u0131 bilgi i\u00e7in  buraya<\/a>  bakabilirsiniz.  Bu basit komut, modeli \u00e7al\u0131\u015ft\u0131r\u0131r ve belirtilen portu a\u00e7ar.<\/p>\n
Avantajlar ve Uygulama Alanlar\u0131<\/h2>\n
Docker Model Runner’\u0131n kullan\u0131m\u0131, bir\u00e7ok avantaj sunar.  \u00d6rne\u011fin, farkl\u0131 LLM’leri kar\u015f\u0131la\u015ft\u0131rmak ve en uygun olan\u0131 se\u00e7mek \u00e7ok daha kolayla\u015f\u0131r.  Ayr\u0131ca, ekip \u00e7al\u0131\u015fmas\u0131 i\u00e7in idealdir, \u00e7\u00fcnk\u00fc herkes ayn\u0131 \u00e7al\u0131\u015fma ortam\u0131n\u0131 kolayca kullanabilir.  Versiyon kontrol\u00fc de kolayla\u015f\u0131r.  LLM’leri yerel olarak \u00e7al\u0131\u015ft\u0131rmak, gizlilik ve g\u00fcvenlik a\u00e7\u0131s\u0131ndan da avantaj sa\u011flar.  \u00d6zellikle hassas verilerle \u00e7al\u0131\u015f\u0131yorsan\u0131z, bulut tabanl\u0131 \u00e7\u00f6z\u00fcmlere g\u00fcvenmek yerine, kendi sunucunuzda \u00e7al\u0131\u015ft\u0131rmak daha g\u00fcvenli olabilir.<\/p>\n
Bununla birlikte, Docker Model Runner’\u0131 kullanman\u0131n baz\u0131 dezavantajlar\u0131 da vard\u0131r.  \u00d6rne\u011fin, b\u00fcy\u00fck modellerin \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131 i\u00e7in g\u00fc\u00e7l\u00fc bir donan\u0131ma ihtiya\u00e7 duyabilirsiniz.  Ayr\u0131ca, Docker’\u0131n temel bilgilerine a\u015fina olman\u0131z gerekebilir.  Ancak, bu dezavantajlar, elde edilen avantajlara k\u0131yasla olduk\u00e7a azd\u0131r.<\/p>\n
Sonu\u00e7<\/h2>\n
Sonu\u00e7 olarak, Docker Model Runner, yerel LLM model \u00e7al\u0131\u015ft\u0131rmay\u0131 b\u00fcy\u00fck \u00f6l\u00e7\u00fcde basitle\u015ftiren ve h\u0131zland\u0131ran g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r.  Karma\u015f\u0131k yap\u0131land\u0131rmalardan kurtulmak ve farkl\u0131 modelleri kolayca test etmek isteyen herkes i\u00e7in ideal bir \u00e7\u00f6z\u00fcmd\u00fcr.  Bu makalede ele ald\u0131\u011f\u0131m\u0131z bilgilerle, kendi LLM projelerinizde Docker Model Runner’\u0131 kullanmaya ba\u015flayabilirsiniz.  Daha fazla bilgi ve uygulama \u00f6rne\u011fi i\u00e7in,  web sitemi<\/a> ziyaret edebilirsiniz.<\/p>\n
#Etiketler: Docker, LLM, B\u00fcy\u00fck Dil Modelleri, Model \u00c7al\u0131\u015ft\u0131rma, Yerel \u00c7al\u0131\u015ft\u0131rma, Docker Model Runner, Yapay Zeka, Makine \u00d6\u011frenmesi, Konteynerle\u015ftirme
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Ancak, bu g\u00fc\u00e7l\u00fc modellerin yerel olarak \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131, genellikle karma\u015f\u0131k ba\u011f\u0131ml\u0131l\u0131klar\u0131 ve yap\u0131land\u0131rma ad\u0131mlar\u0131n\u0131 gerektiren zorlu bir s\u00fcre\u00e7 olabiliyordu. Neyse ki, Docker gibi konteynerle\u015ftirme teknolojileri bu sorunu \u00f6nemli \u00f6l\u00e7\u00fcde hafifletiyor. Bu makalede, Docker'\u0131 kullanarak yerel LLM model y\u00fcr\u00fctmenin nas\u0131l kolayla\u015ft\u0131r\u0131laca\u011f\u0131n\u0131, \u00f6zellikle de Docker Model Runner'\u0131 kullanarak, ayr\u0131nt\u0131l\u0131 olarak ele alaca\u011f\u0131z.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Docker ile Yerel LLM Model \u00c7al\u0131\u015ft\u0131rman\u0131n Basitle\u015ftirilmesi\" \/>\n<meta property=\"og:description\" content=\"B\u00fcy\u00fck dil modelleri (LLM'ler) son y\u0131llarda inan\u0131lmaz bir ilerleme kaydetti. Ancak, bu g\u00fc\u00e7l\u00fc modellerin yerel olarak \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131, genellikle karma\u015f\u0131k ba\u011f\u0131ml\u0131l\u0131klar\u0131 ve yap\u0131land\u0131rma ad\u0131mlar\u0131n\u0131 gerektiren zorlu bir s\u00fcre\u00e7 olabiliyordu. Neyse ki, Docker gibi konteynerle\u015ftirme teknolojileri bu sorunu \u00f6nemli \u00f6l\u00e7\u00fcde hafifletiyor. Bu makalede, Docker'\u0131 kullanarak yerel LLM model y\u00fcr\u00fctmenin nas\u0131l kolayla\u015ft\u0131r\u0131laca\u011f\u0131n\u0131, \u00f6zellikle de Docker Model Runner'\u0131 kullanarak, ayr\u0131nt\u0131l\u0131 olarak ele alaca\u011f\u0131z.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/\" \/>\n<meta property=\"og:site_name\" content=\"Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" \/>\n<meta property=\"article:published_time\" content=\"2025-04-23T05:00:15+00:00\" \/>\n<meta name=\"author\" content=\"Fatih Soysal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Fatih Soysal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/\"},\"author\":{\"name\":\"Fatih Soysal\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"headline\":\"Docker ile Yerel LLM Model \u00c7al\u0131\u015ft\u0131rman\u0131n Basitle\u015ftirilmesi\",\"datePublished\":\"2025-04-23T05:00:15+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/\"},\"wordCount\":615,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/#respond\"]}],\"copyrightYear\":\"2025\",\"copyrightHolder\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/docker-ile-yerel-llm-model-calistirmanin-basitlestirilmesi\/\",\"name\":\"Docker ile Yerel LLM Model \u00c7al\u0131\u015ft\u0131rman\u0131n Basitle\u015ftirilmesi\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#website\"},\"datePublished\":\"2025-04-23T05:00:15+00:00\",\"description\":\"B\u00fcy\u00fck dil modelleri (LLM'ler) son y\u0131llarda inan\u0131lmaz bir ilerleme kaydetti. 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