{"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":"How to Use Hugging Face Transformers, Installation of BERT Document Vector Processing Module - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"GQrGqq68I9\"><a href=\"https:\/\/atmokpo.com\/w\/36065\/\">How to Use Hugging Face Transformers, Installation of BERT Document Vector Processing Module<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/atmokpo.com\/w\/36065\/embed\/#?secret=GQrGqq68I9\" width=\"600\" height=\"338\" title=\"&#8220;How to Use Hugging Face Transformers, Installation of BERT Document Vector Processing Module&#8221; &#8212; \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" data-secret=\"GQrGqq68I9\" 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":"With the advancement of deep learning and natural language processing (NLP), the Hugging Face transformers library has become an essential tool for many data scientists and developers. In particular, the BERT (Bidirectional Encoder Representations from Transformers) model has demonstrated powerful performance in understanding context and is widely used in NLP tasks. In this article, we &hellip; \ub354 \ubcf4\uae30 \"\""}