{"id":2874,"date":"2026-05-04T13:15:40","date_gmt":"2026-05-04T10:15:40","guid":{"rendered":"https:\/\/shareai.now\/?p=2874"},"modified":"2026-05-04T13:15:43","modified_gmt":"2026-05-04T10:15:43","slug":"hugging-face-alternatifleri","status":"publish","type":"post","link":"https:\/\/shareai.now\/tr\/blog\/alternatifler\/hugging-face-alternatifleri\/","title":{"rendered":"En \u0130yi Hugging Face Alternatifleri 2026: API'ler ve Da\u011f\u0131t\u0131m i\u00e7in 6 Pratik Se\u00e7enek"},"content":{"rendered":"<p>Ekipler genellikle Hugging Face alternatiflerini aramaya, ya bir API arac\u0131l\u0131\u011f\u0131yla a\u00e7\u0131k modellere daha basit eri\u015fim ya da bu modellerin \u00fcretimde nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131 \u00fczerinde daha fazla kontrol gerekti\u011finde ba\u015flar. Bunlar ili\u015fkili ihtiya\u00e7lard\u0131r, ancak ayn\u0131 karar de\u011fildir.<\/p>\n\n\n\n<p>Baz\u0131 platformlar, sa\u011flay\u0131c\u0131 karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 azaltarak bir\u00e7ok model aras\u0131nda istekleri y\u00f6nlendirmenize yard\u0131mc\u0131 olur. Di\u011ferleri ise GPU i\u015f y\u00fcklerini paketlemenize, bar\u0131nd\u0131rman\u0131za, ince ayar yapman\u0131za veya kendi kendinize y\u00f6netmenize yard\u0131mc\u0131 olur. Do\u011fru se\u00e7im, API eri\u015fimine, da\u011f\u0131t\u0131m kontrol\u00fcne veya altyap\u0131 y\u0131\u011f\u0131n\u0131n\u0131n daha fazlas\u0131na sahip olmaya ne kadar \u00f6nem verdi\u011finize ba\u011fl\u0131d\u0131r.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Hugging Face alternatifini se\u00e7meden \u00f6nce kar\u015f\u0131la\u015ft\u0131r\u0131lacaklar<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Model eri\u015fimi ve uyumluluk<\/h3>\n\n\n\n<p>Ekibiniz a\u00e7\u0131k modellere h\u0131zl\u0131 eri\u015fim istiyorsa, katalo\u011fun ne kadar geni\u015f oldu\u011funu ve sa\u011flay\u0131c\u0131lar\u0131 veya modelleri daha sonra de\u011fi\u015ftirmenin ne kadar kolay oldu\u011funu kontrol edin. Tek bir API ve bir\u00e7ok model se\u00e7ene\u011fi sunan bir platform, entegrasyon karma\u015fas\u0131n\u0131 azalt\u0131r.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Y\u00f6nlendirme ve yedekleme<\/h3>\n\n\n\n<p>Baz\u0131 ekipler yaln\u0131zca tek bir bar\u0131nd\u0131r\u0131lan u\u00e7 noktaya ihtiya\u00e7 duyar. Di\u011ferleri ise y\u00f6nlendirme mant\u0131\u011f\u0131, geri d\u00f6n\u00fc\u015f davran\u0131\u015f\u0131 ve sa\u011flay\u0131c\u0131lar aras\u0131nda fiyat veya kullan\u0131labilirlik g\u00f6r\u00fcn\u00fcrl\u00fc\u011f\u00fc ister. Bu, yapay zeka kullan\u0131m\u0131 deneylerden \u00fcretime ge\u00e7ti\u011finde daha \u00f6nemli hale gelir.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Fiyatland\u0131rma ve kullan\u0131m kontrol\u00fc<\/h3>\n\n\n\n<p>Bar\u0131nd\u0131r\u0131lan \u00e7\u0131kar\u0131m \u00fcr\u00fcnleriyle ba\u015flamak kolayd\u0131r, ancak fiyatland\u0131rma mekanikleri de\u011fi\u015fiklik g\u00f6sterir. Baz\u0131lar\u0131 token ba\u015f\u0131na, baz\u0131lar\u0131 \u00e7al\u0131\u015fma s\u00fcresine g\u00f6re faturaland\u0131r\u0131r ve baz\u0131lar\u0131 kendi altyap\u0131 harcamalar\u0131n\u0131z\u0131 y\u00f6netmenizi bekler. Faturaland\u0131rma modelinin uygulaman\u0131z\u0131n yapay zekay\u0131 nas\u0131l kulland\u0131\u011f\u0131na uygun oldu\u011fundan emin olun.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Da\u011f\u0131t\u0131m kontrol\u00fc<\/h3>\n\n\n\n<p>Modelleri ince ayar yapman\u0131z, \u00f6zel konteynerler \u00e7al\u0131\u015ft\u0131rman\u0131z veya i\u015f y\u00fcklerini kendi bulutunuzda tutman\u0131z gerekiyorsa, saf API \u00fcr\u00fcnleri s\u0131n\u0131rlay\u0131c\u0131 gelebilir. Bu durumda, da\u011f\u0131t\u0131m platformlar\u0131 ve model sunma \u00e7er\u00e7eveleri \u00e7\u0131kar\u0131m pazar yerlerinden daha alakal\u0131 hale gelir.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">G\u00f6zlemlenebilirlik ve operat\u00f6r i\u015f ak\u0131\u015f\u0131<\/h3>\n\n\n\n<p>Trafik artt\u0131\u011f\u0131nda g\u00fcnl\u00fckler, kullan\u0131m g\u00f6r\u00fcn\u00fcrl\u00fc\u011f\u00fc ve hata ay\u0131klama h\u0131z\u0131 \u00f6nemlidir. \u00dcr\u00fcn y\u0131\u011f\u0131n\u0131n \u00e7ok fazlas\u0131n\u0131 gizlerse, operasyonlar daha sonra zorla\u015fabilir.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Hugging Face genel bak\u0131\u015f<\/h2>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/shareai.now\/wp-content\/uploads\/2025\/09\/huggingface.jpg\" alt=\"Hugging Face alternatifleri Hugging Face ekran g\u00f6r\u00fcnt\u00fcs\u00fc\"\/><figcaption>Kar\u015f\u0131la\u015ft\u0131rma ba\u011flam\u0131 i\u00e7in Hugging Face ekran g\u00f6r\u00fcnt\u00fcs\u00fc.<\/figcaption><\/figure>\n\n\n\n<p>Hugging Face, a\u00e7\u0131k model ekosisteminin \u00f6nemli bir par\u00e7as\u0131 olmaya devam ediyor. Model ke\u015ffi, a\u00e7\u0131k kaynak i\u015f birli\u011fi ve bar\u0131nd\u0131r\u0131lan \u00e7\u0131kar\u0131m \u00fcr\u00fcnleri gibi alanlarda yayg\u0131n olarak kullan\u0131l\u0131yor. <a href=\"https:\/\/huggingface.co\/docs\/huggingface_hub\/en\/guides\/inference_endpoints\" rel=\"nofollow noopener\" target=\"_blank\">\u00c7\u0131kar\u0131m U\u00e7 Noktalar\u0131<\/a>. Ancak bir\u00e7ok ekip tek bir varsay\u0131lan yap\u0131land\u0131rmay\u0131 a\u015far.<\/p>\n\n\n\n<p>Al\u0131\u015f\u0131lm\u0131\u015f bask\u0131 noktalar\u0131 tahmin edilebilir: daha esnek y\u00f6nlendirme, farkl\u0131 bir fiyatland\u0131rma modeli, daha kolay \u00fcretim API'leri veya da\u011f\u0131t\u0131m ve altyap\u0131 \u00fczerinde daha fazla kontrol isterler.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">En \u0130yi Hugging Face Alternatifleri<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">ShareAI<\/h3>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/shareai.now\/wp-content\/uploads\/2025\/09\/shareai.jpg\" alt=\"Hugging Face alternatifleri ShareAI ekran g\u00f6r\u00fcnt\u00fcs\u00fc\"\/><figcaption>Kar\u015f\u0131la\u015ft\u0131rma ba\u011flam\u0131 i\u00e7in ShareAI ekran g\u00f6r\u00fcnt\u00fcs\u00fc.<\/figcaption><\/figure>\n\n\n\n<p>ShareAI, tek bir API arac\u0131l\u0131\u011f\u0131yla bir\u00e7ok modele daha basit bir \u015fekilde eri\u015fmek, pazar yeri sinyallerini kar\u015f\u0131la\u015ft\u0131rmak ve birden fazla sa\u011flay\u0131c\u0131 entegrasyonunu kendiniz birle\u015ftirmeden trafik y\u00f6nlendirmek istedi\u011finizde en uygun se\u00e7enektir.<\/p>\n\n\n\n<p>\u00dcretim AI \u00f6zellikleri geli\u015ftiren ekipler i\u00e7in cazibesi a\u00e7\u0131kt\u0131r: tek bir entegrasyon, 150+ model, ak\u0131ll\u0131 y\u00f6nlendirme, yedekleme ve pazar yerindeki se\u00e7eneklere daha net bir g\u00f6r\u00fcn\u00fcrl\u00fck. Mevcut y\u00f6nlendirme se\u00e7eneklerini <a href=\"https:\/\/shareai.now\/models\/?utm_source=blog&#038;utm_medium=content&#038;utm_campaign=hugging-face-alternatives\">model pazar\u0131 de\u011fil<\/a>, istekleri test edebilirsiniz <a href=\"https:\/\/console.shareai.now\/chat\/?utm_source=shareai.now&#038;utm_medium=content&#038;utm_campaign=hugging-face-alternatives\">Playground'da<\/a>, ve g\u00f6zden ge\u00e7irin <a href=\"https:\/\/shareai.now\/documentation\/?utm_source=blog&#038;utm_medium=content&#038;utm_campaign=hugging-face-alternatives\">belgelerde<\/a> uygulaman\u0131za ba\u011flamadan \u00f6nce inceleyebilirsiniz.<\/p>\n\n\n\n<p>ShareAI'nin \u00f6ne \u00e7\u0131kt\u0131\u011f\u0131 yer, kendi kendine bar\u0131nd\u0131r\u0131lan e\u011fitim altyap\u0131s\u0131 de\u011fildir. A\u00e7\u0131k model esnekli\u011fi isteyen ancak API eri\u015fimini ve sa\u011flay\u0131c\u0131 se\u00e7imini s\u0131f\u0131rdan yeniden olu\u015fturmak istemeyen ekipler i\u00e7in y\u00f6nlendirme, eri\u015fim, faturaland\u0131rma ve pazar yeri katman\u0131d\u0131r. Ayr\u0131ca, ShareAI d\u0131\u015f\u0131nda zaten sahip olduklar\u0131 bir uygulamadan AI \u00e7\u0131kar\u0131m trafi\u011fini paraya \u00e7evirmek isteyen Geli\u015ftiriciler i\u00e7in de g\u00fc\u00e7l\u00fc bir uyum sa\u011flar.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Northflank<\/h3>\n\n\n\n<p>\u00d6nceli\u011finiz modelleri ve y\u0131\u011f\u0131n\u0131n geri kalan\u0131n\u0131 kontrol etti\u011finiz bir altyap\u0131da \u00e7al\u0131\u015ft\u0131rmak oldu\u011funda Northflank daha g\u00fc\u00e7l\u00fc bir se\u00e7enektir. Konumland\u0131rmas\u0131, tam y\u0131\u011f\u0131n da\u011f\u0131t\u0131m\u0131, GPU i\u015f y\u00fckleri, BYOC ve g\u00fcvenli \u00e7al\u0131\u015fma zaman\u0131 izolasyonu \u00fczerine odaklan\u0131r; bu, ekibinizin API'leri, \u00e7al\u0131\u015fanlar\u0131, veritabanlar\u0131n\u0131 ve model i\u015f y\u00fcklerini bir arada \u00e7al\u0131\u015ft\u0131rmas\u0131 gerekti\u011finde faydal\u0131d\u0131r.<\/p>\n\n\n\n<p>Bu, temel sorun model eri\u015fim soyutlamas\u0131ndan ziyade da\u011f\u0131t\u0131m sahipli\u011fi oldu\u011funda Northflank'i ShareAI'den daha uygun hale getirir. \u0130nce ayar i\u015fleri, uzun s\u00fcreli GPU hizmetleri ve uygulama altyap\u0131s\u0131n\u0131 tek bir yerde ihtiya\u00e7 duyuyorsan\u0131z, Northflank k\u0131sa listenizde yer almal\u0131d\u0131r.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">BentoML<\/h3>\n\n\n\n<p>BentoML, modelleri Python hizmetlerine d\u00f6n\u00fc\u015ft\u00fcrmek ve paketleme ile sunum \u00fczerinde daha fazla kontrol isteyen ekipler i\u00e7in iyi bir se\u00e7enektir. Platformu model sunumu ve orkestrasyonu \u00fczerine odaklanm\u0131\u015ft\u0131r ve \u00f6zellikle ekibiniz Python \u00f6ncelikli i\u015f ak\u0131\u015flar\u0131na al\u0131\u015fk\u0131nsa ve kendi sunum katman\u0131n\u0131 \u015fekillendirmek istiyorsa faydal\u0131d\u0131r.<\/p>\n\n\n\n<p>ShareAI ile kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda, BentoML m\u00fchendislik ekibinizden daha fazlas\u0131n\u0131 talep eder. Hugging Face bar\u0131nd\u0131r\u0131lan \u00e7\u0131kar\u0131m ile kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda, size daha fazla kontrol sa\u011flar. Bu, hizmet katman\u0131na sahip olmak isteyen ancak ilk g\u00fcnden tam bir platform yeniden yaz\u0131m\u0131na taahh\u00fct etmek istemeyen ekipler i\u00e7in g\u00fc\u00e7l\u00fc bir orta yol haline getirir.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\u00c7o\u011falt<\/h3>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/shareai.now\/wp-content\/uploads\/2025\/09\/replicate.jpg\" alt=\"Hugging Face alternatifleri Replicate ekran g\u00f6r\u00fcnt\u00fcs\u00fc\"\/><figcaption>Kar\u015f\u0131la\u015ft\u0131rma ba\u011flam\u0131 i\u00e7in Replicate ekran g\u00f6r\u00fcnt\u00fcs\u00fc.<\/figcaption><\/figure>\n\n\n\n<p>Replicate, a\u00e7\u0131k kaynakl\u0131 modelleri bar\u0131nd\u0131r\u0131lan bir API arac\u0131l\u0131\u011f\u0131yla \u00e7al\u0131\u015ft\u0131rman\u0131n en basit yollar\u0131ndan biridir. Belgeleri, altyap\u0131y\u0131 y\u00f6netmeden makine \u00f6\u011frenimi modellerini \u00e7al\u0131\u015ft\u0131rmak i\u00e7in bir bulut API'si olarak konumland\u0131r\u0131r, bu nedenle h\u0131zl\u0131 deneyler ve hafif \u00fcretim kullan\u0131m durumlar\u0131 i\u00e7in iyi \u00e7al\u0131\u015f\u0131r.<\/p>\n\n\n\n<p>Taviz kontrol \u00fczerinedir. Replicate, h\u0131z ve kolayl\u0131k istedi\u011finizde harikad\u0131r. \u00c7ok sa\u011flay\u0131c\u0131l\u0131 y\u00f6nlendirme, daha derin da\u011f\u0131t\u0131m kontrol\u00fc veya bir\u00e7ok rota ve faturalama se\u00e7ene\u011fi aras\u0131nda bir operat\u00f6r g\u00f6r\u00fcn\u00fcm\u00fc gerekti\u011finde daha az caziptir.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Birlikte AI<\/h3>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/shareai.now\/wp-content\/uploads\/2025\/09\/togetherai.jpg\" alt=\"Hugging Face alternatifleri Together AI ekran g\u00f6r\u00fcnt\u00fcs\u00fc\"\/><figcaption>Kar\u015f\u0131la\u015ft\u0131rma ba\u011flam\u0131 i\u00e7in Together AI ekran g\u00f6r\u00fcnt\u00fcs\u00fc.<\/figcaption><\/figure>\n\n\n\n<p>Together AI, geni\u015f bir a\u00e7\u0131k kaynakl\u0131 model setine API eri\u015fimi istiyorsan\u0131z ve daha sonra ince ayar veya \u00f6zel u\u00e7 noktalar isteyebilirsiniz, g\u00fc\u00e7l\u00fc bir se\u00e7enektir. Belgeleri, OpenAI uyumlu \u00e7\u0131kar\u0131m\u0131 ve geni\u015f bir a\u00e7\u0131k model katalo\u011fu deste\u011fini vurgular, bu da geli\u015ftiricilerin h\u0131zl\u0131 bir \u015fekilde benimsemesini kolayla\u015ft\u0131r\u0131r.<\/p>\n\n\n\n<p>Hugging Face ile kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda, Together AI, yaln\u0131zca \u00e7\u0131kar\u0131m API'leri isteyen \u00fcr\u00fcn ekipleri i\u00e7in daha do\u011frudan hissedilebilir. ShareAI ile kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda, daha \u00e7ok tek platform sa\u011flay\u0131c\u0131 se\u00e7imi gibidir, oysa ShareAI, daha geni\u015f rota kar\u015f\u0131la\u015ft\u0131rmas\u0131 ve bir pazar yeri tarz\u0131 eri\u015fim katman\u0131 isteyen ekipler i\u00e7in daha uygundur.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">RunPod<\/h3>\n\n\n\n<p>RunPod, tam bir PaaS'tan daha az platform y\u00fck\u00fc ile GPU destekli konteynerler isteyen ekipler i\u00e7in uygundur. Model i\u015f y\u00fcklerini h\u0131zl\u0131 bir \u015fekilde \u00e7al\u0131\u015ft\u0131rmak istedi\u011finizde ve da\u011f\u0131t\u0131m ve orkestrasyon kararlar\u0131n\u0131 kendiniz \u00fcstlenmekte rahat oldu\u011funuzda pratiktir.<\/p>\n\n\n\n<p>Bu, \u00fcr\u00fcn ekiplerinden \u00e7ok hesaplama odakl\u0131 ekipler i\u00e7in daha iyi bir yoldur. \u00c7al\u0131\u015fman\u0131z altyap\u0131 ve konteyner kontrol\u00fc ile ba\u015fl\u0131yorsa, RunPod mant\u0131kl\u0131d\u0131r. \u00c7al\u0131\u015fman\u0131z uygulama entegrasyon h\u0131z\u0131 ile ba\u015fl\u0131yorsa, ShareAI veya Together AI genellikle operasyonelle\u015ftirmek i\u00e7in daha h\u0131zl\u0131 olacakt\u0131r.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">ShareAI'nin uyumu<\/h2>\n\n\n\n<p>ShareAI, her Hugging Face i\u015f ak\u0131\u015f\u0131n\u0131n yerine ge\u00e7mez ve bu tam olarak neden net bir \u015fekilde konumland\u0131r\u0131lmas\u0131 gerekti\u011fidir.<\/p>\n\n\n\n<p>Ekibiniz kendi GPU'lar\u0131n\u0131zda \u00f6zel modelleri ince ayar yapmak, karma\u015f\u0131k e\u011fitim i\u015fleri bar\u0131nd\u0131rmak veya bu i\u015f y\u00fckleri etraf\u0131nda tam bir uygulama platformu \u00e7al\u0131\u015ft\u0131rmak istiyorsa, Northflank, BentoML veya RunPod daha uygun olabilir.<\/p>\n\n\n\n<p>Ekibiniz bir API ile AI \u00f6zellikleri g\u00f6ndermek, model se\u00e7eneklerini daha kolay kar\u015f\u0131la\u015ft\u0131rmak, sa\u011flay\u0131c\u0131 yay\u0131l\u0131m\u0131n\u0131 azaltmak ve y\u00f6nlendirme ve hata tolerans\u0131n\u0131 esnek tutmak istiyorsa, ShareAI daha iyi bir alternatiftir.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">ShareAI yolunu deneyin<\/h2>\n\n\n\n<p>Daha fazla esneklik istedi\u011finiz i\u00e7in tam bir altyap\u0131 projesine giri\u015fmeden Hugging Face alternatiflerini de\u011ferlendiriyorsan\u0131z, ShareAI'deki canl\u0131 model se\u00e7eneklerini kar\u015f\u0131la\u015ft\u0131rarak ba\u015flay\u0131n. En h\u0131zl\u0131 sonraki ad\u0131m <a href=\"https:\/\/shareai.now\/models\/?utm_source=blog&#038;utm_medium=content&#038;utm_campaign=hugging-face-alternatives\">modelleri g\u00f6zden ge\u00e7ir<\/a>, <a href=\"https:\/\/console.shareai.now\/chat\/?utm_source=shareai.now&#038;utm_medium=content&#038;utm_campaign=hugging-face-alternatives\">Playground'da bir iste\u011fi test edin<\/a>, veya okuyun <a href=\"https:\/\/shareai.now\/documentation\/?utm_source=blog&#038;utm_medium=content&#038;utm_campaign=hugging-face-alternatives\">API belgelerini<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"<p>Model eri\u015fimi, y\u00f6nlendirme, bar\u0131nd\u0131r\u0131lan \u00e7\u0131kar\u0131m ve da\u011f\u0131t\u0131m kontrol\u00fc i\u00e7in pratik Hugging Face alternatiflerini kar\u015f\u0131la\u015ft\u0131r\u0131n, ayr\u0131ca ShareAI'nin en iyi uydu\u011fu yeri de\u011ferlendirin.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"cta-title":"Explore AI Models","cta-description":"Compare price, latency, and availability across providers.","cta-button-text":"Browse Models","cta-button-link":"https:\/\/shareai.now\/models\/?utm_source=blog&amp;utm_medium=content&amp;utm_campaign=hugging-face-alternatives","rank_math_title":"Hugging Face Alternatives [sai_current_year]: 6 Practical Options for APIs and Deployment","rank_math_description":"Compare 6 practical Hugging Face alternatives for model access, routing, hosted inference, and deployment control, including where ShareAI fits best.","rank_math_focus_keyword":"Hugging Face alternatives","footnotes":""},"categories":[38,6],"tags":[42,58,44,51,53,54],"class_list":["post-2874","post","type-post","status-publish","format-standard","hentry","category-alternatives","category-insights","tag-ai-api-routing","tag-ai-model-marketplace","tag-model-failover","tag-model-routing","tag-open-weight-ai","tag-self-hosted-ai"],"_links":{"self":[{"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/posts\/2874","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/comments?post=2874"}],"version-history":[{"count":2,"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/posts\/2874\/revisions"}],"predecessor-version":[{"id":2876,"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/posts\/2874\/revisions\/2876"}],"wp:attachment":[{"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/media?parent=2874"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/categories?post=2874"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/shareai.now\/tr\/api\/wp\/v2\/tags?post=2874"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}