{"id":247,"date":"2024-11-28T07:00:20","date_gmt":"2024-11-28T07:00:20","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2024\/11\/28\/how-to-prune-llama-3-2-and-similar-large-language-models-cf18e9a2afb6\/"},"modified":"2024-11-28T07:00:20","modified_gmt":"2024-11-28T07:00:20","slug":"how-to-prune-llama-3-2-and-similar-large-language-models-cf18e9a2afb6","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2024\/11\/28\/how-to-prune-llama-3-2-and-similar-large-language-models-cf18e9a2afb6\/","title":{"rendered":"How to Prune LLaMA 3.2 and Similar Large Language Models"},"content":{"rendered":"<p>    How to Prune LLaMA 3.2 and Similar Large Language Models<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<div class=\"medium-feed-item\">\n<p class=\"medium-feed-image\"><a href=\"https:\/\/towardsdatascience.com\/how-to-prune-llama-3-2-and-similar-large-language-models-cf18e9a2afb6\"><img decoding=\"async\" src=\"https:\/\/cdn-images-1.medium.com\/max\/1024\/0*fGdWE8ISkmax5Cjb\" width=\"1024\"><\/a><\/p>\n<p class=\"medium-feed-snippet\">This article explores a structured pruning technique for state-of-the-art models, that uses a GLU architecture, enabling the creation of\u2026<\/p>\n<p class=\"medium-feed-link\"><a href=\"https:\/\/towardsdatascience.com\/how-to-prune-llama-3-2-and-similar-large-language-models-cf18e9a2afb6\">Continue reading on Towards Data Science \u00bb<\/a><\/p>\n<\/div>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Pere Martra<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/medium.com\/m\/global-identity-2?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Fhow-to-prune-llama-3-2-and-similar-large-language-models-cf18e9a2afb6\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>How to Prune LLaMA 3.2 and Similar Large Language Models This article explores a structured pruning technique for state-of-the-art models, that uses a GLU architecture, enabling the creation of\u2026 Continue reading on Towards Data Science \u00bb Pere Martra Go to original source<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,166,71,164,165,167],"tags":[7,73,168],"class_list":["post-247","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-hands-on-tutorials","category-large-language-models","category-llama-3","category-pruning","category-small-language-model","tag-how","tag-models","tag-prune"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/247"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=247"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/247\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=247"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=247"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=247"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}