{"id":616,"date":"2026-04-09T12:23:28","date_gmt":"2026-04-09T09:23:28","guid":{"rendered":"https:\/\/shareai.now\/?p=616"},"modified":"2026-04-14T03:21:11","modified_gmt":"2026-04-14T00:21:11","slug":"embeddinggemma-shareai-300m-model-embedding","status":"publish","type":"post","link":"https:\/\/shareai.now\/jv\/blog\/warta\/embeddinggemma-shareai-300m-model-embedding\/","title":{"rendered":"EmbeddingGemma ing ShareAI: 300M Multilingual Embeddings"},"content":{"rendered":"<h1 class=\"wp-block-heading\">EmbeddingGemma saiki ana ing ShareAI<\/h1>\n\n\n\n<p>Kita ngumumake yen <strong>EmbeddingGemma<\/strong>, model embedding kompak saka Google, saiki kasedhiya ing ShareAI.<\/p>\n\n\n\n<p>Ing <strong>300 yuta parameter<\/strong>, EmbeddingGemma menehi kinerja paling apik kanggo ukuran\u00e9. Iki dibangun saka <strong>Gemma 3<\/strong> kanthi <strong>T5Gemma inisialisasi<\/strong> lan nggunakake riset lan teknologi sing padha ing balik <strong>Gemini<\/strong> model. Model iki ngasilake representasi vektor saka teks, nggawe cocok kanggo tugas telusuran lan pengambilan, kalebu <strong>klasifikasi<\/strong>, <strong>klustering<\/strong>, lan <strong>kesamaan semantik<\/strong>. Iki dilatih nganggo data ing <strong>100+ basa sing diucapak\u00e9<\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Napa iki penting<\/h2>\n\n\n\n<p>Ukuran model sing cilik lan fokus ing piranti nggawe praktis kanggo digunakak\u00e9 ing lingkungan kanthi sumber daya sing winates\u2014<strong>telpon seluler, laptop, utawa desktop<\/strong>\u2014demokratisasi akses menyang model AI paling anyar lan nyengkuyung inovasi kanggo kabeh wong.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Patokan<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/shareai.now\/wp-content\/uploads\/2025\/09\/embeddinggemma-1024x576.png\" alt=\"\" class=\"wp-image-1547\"\/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Dataset pelatihan<\/h2>\n\n\n\n<p>EmbeddingGemma dilatih nganggo data ing 100+ basa sing diucapak\u00e9.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Dokumen web<\/strong><br>Koleksi teks web sing beragam njamin paparan gaya linguistik, topik, lan kosakata sing luas. Dataset iki kalebu konten ing <strong>100+ basa<\/strong>.<\/li>\n\n\n\n<li><strong>Kode lan dokumen teknis<\/strong><br>Kalebu basa pemrograman lan konten ilmiah khusus mbantu model sinau struktur lan pola sing ningkatak\u00e9 pangerten kode lan pitakon teknis.<\/li>\n\n\n\n<li><strong>Data sintetik lan tugas khusus<\/strong><br>Data sintetik sing dikurasi ngajari katrampilan khusus kanggo pengambilan informasi, klasifikasi, lan analisis sentimen, nyetel kinerja kanggo aplikasi embedding umum.<\/li>\n<\/ul>\n\n\n\n<p>Kombinasi saka sumber sing maneka warna iki penting kanggo model embedding multibasa sing kuat sing bisa nangani macem-macem tugas lan format data.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Apa sing bisa sampeyan bangun<\/h2>\n\n\n\n<p>Gunakake EmbeddingGemma kanggo <strong>panelusuran lan pangambilan<\/strong>, <strong>kesamaan semantik<\/strong>, <strong>pipeline klasifikasi<\/strong>, lan <strong>klustering<\/strong>\u2014utamane nalika sampeyan butuh embedding kualitas dhuwur sing bisa mlaku ing piranti sing diwatesi.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Referensi<\/h3>\n\n\n\n<p><a href=\"https:\/\/ai.google.dev\/gemma\/docs\/embeddinggemma\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Dokumentasi<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Saiki kasedhiya ing ShareAI.<\/strong><\/h2>\n\n\n\n<p>Lakokna. Coba. Kirim.<\/p>\n\n\n\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>EmbeddingGemma saiki ana ing ShareAI Kita ngumumake yen EmbeddingGemma, model embedding kompak saka Google, saiki kasedhiya ing ShareAI. Kanthi 300 yuta parameter, EmbeddingGemma nyedhiyakake kinerja paling anyar kanggo ukurane. Iki dibangun saka Gemma 3 kanthi inisialisasi T5Gemma lan nggunakake riset lan teknologi sing padha karo model Gemini. Model iki ngasilake representasi vektor saka [\u2026]<\/p>","protected":false},"author":1,"featured_media":617,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"cta-title":"Try EmbeddingGemma on ShareAI","cta-description":"Spin up the 300M multilingual embedding model in the ShareAI Playground or integrate it via API for search, similarity, and clustering.","cta-button-text":"Launch Playground","cta-button-link":"","rank_math_title":"EmbeddingGemma on ShareAI: 300M Multilingual Embeddings","rank_math_description":"EmbeddingGemma is now on ShareAI: a 300M open embedding model from Google for search, retrieval, clustering and semantic similarity\u2014multilingual, on-device.","rank_math_focus_keyword":"EmbeddingGemma","footnotes":""},"categories":[7],"tags":[],"class_list":["post-616","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/posts\/616","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/comments?post=616"}],"version-history":[{"count":3,"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/posts\/616\/revisions"}],"predecessor-version":[{"id":2207,"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/posts\/616\/revisions\/2207"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/media\/617"}],"wp:attachment":[{"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/media?parent=616"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/categories?post=616"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/shareai.now\/jv\/api\/wp\/v2\/tags?post=616"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}