{"version":"1.0","provider_name":"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8","provider_url":"https:\/\/atmokpo.com\/w","author_name":"root","author_url":"https:\/\/atmokpo.com\/w\/author\/root\/","title":"Introduction to Using Hugging Face Transformers, BERT Ensemble Learning Library Setup - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"kvlGfWuP2B\"><a href=\"https:\/\/atmokpo.com\/w\/36087\/\">Introduction to Using Hugging Face Transformers, BERT Ensemble Learning Library Setup<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/atmokpo.com\/w\/36087\/embed\/#?secret=kvlGfWuP2B\" width=\"600\" height=\"338\" title=\"&#8220;Introduction to Using Hugging Face Transformers, BERT Ensemble Learning Library Setup&#8221; &#8212; \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" data-secret=\"kvlGfWuP2B\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/atmokpo.com\/w\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"Recently, natural language processing (NLP) has become a major challenge in the field of artificial intelligence, with models like BERT (Bidirectional Encoder Representations from Transformers) leading innovations in this area. The BERT model provides the ability to understand the context of words in both directions, enabling more sophisticated approaches to solving natural language problems. In &hellip; \ub354 \ubcf4\uae30 \"\""}