{"id":29678,"date":"2024-10-28T01:56:03","date_gmt":"2024-10-28T01:56:03","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=29678"},"modified":"2024-11-26T06:51:45","modified_gmt":"2024-11-26T06:51:45","slug":"%ed%97%88%ea%b9%85%ed%8e%98%ec%9d%b4%ec%8a%a4-%ed%8a%b8%eb%a0%8c%ec%8a%a4%ed%8f%ac%eb%a8%b8-%ed%99%9c%ec%9a%a9%ea%b0%95%ec%a2%8c-%ec%9c%84%ed%82%a4%ed%94%bc%eb%94%94%ec%95%84-%ec%98%81%eb%ac%b8","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/29678\/","title":{"rendered":"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc704\ud0a4\ud53c\ub514\uc544 \uc601\ubb38 \ud0a4\uc6cc\ub4dc \uac80\uc0c9"},"content":{"rendered":"

<\/p>\n

\n

\ub525\ub7ec\ub2dd\uacfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uac15\ub825\ud55c \ub3c4\uad6c\ub85c \uc790\ub9ac \uc7a1\uc558\uc2b5\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face Transformers\uc640 \ud568\uaed8 Wikipedia API\ub97c \ud65c\uc6a9\ud558\uc5ec \uc8fc\uc5b4\uc9c4 \ud0a4\uc6cc\ub4dc\ub85c \uc704\ud0a4\ud53c\ub514\uc544\uc5d0\uc11c \uc801\uc808\ud55c \ubb38\uc11c\ub97c \uac80\uc0c9\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/p>\n

1. Hugging Face Transformers\ub780?<\/h2>\n

Hugging Face\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc758 \ud559\uc2b5, \ucd94\ub860 \ubc0f \ubc30\ud3ec\ub97c \uc704\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc81c\uacf5\ud558\ub294 \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4. Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \uc27d\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\uac8c \ud574\uc8fc\uba70, PyTorch \ubc0f TensorFlow\uc640 \ud638\ud658\ub429\ub2c8\ub2e4. \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud1b5\ud574 \ub2e4\uc591\ud55c NLP \uc791\uc5c5\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ud14d\uc2a4\ud2b8 \ubd84\ub958, \uc9c8\ubb38 \ub2f5\ubcc0, \ud14d\uc2a4\ud2b8 \uc0dd\uc131 \ub4f1 \ub2e4\uc591\ud55c \ud0dc\uc2a4\ud06c\uc5d0\uc11c \uc131\ub2a5\uc744 \ubc1c\ud718\ud569\ub2c8\ub2e4.<\/p>\n

2. \uc704\ud0a4\ud53c\ub514\uc544 API \uc18c\uac1c<\/h2>\n

\uc704\ud0a4\ud53c\ub514\uc544\ub294 \uac1c\ubc29\ud615 \uc628\ub77c\uc778 \ubc31\uacfc\uc0ac\uc804\uc73c\ub85c, \ub2e4\uc591\ud55c \uc8fc\uc81c\uc5d0 \ub300\ud55c \uc815\ubcf4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc704\ud0a4\ud53c\ub514\uc544\ub294 API\ub97c \ud1b5\ud574 \uc0ac\uc6a9\uc790\ub4e4\uc774 \ud504\ub85c\uadf8\ub7a8\uc801\uc73c\ub85c \uc815\ubcf4\ub97c \uac80\uc0c9\ud560 \uc218 \uc788\ub3c4\ub85d \uc9c0\uc6d0\ud569\ub2c8\ub2e4. API\ub97c \ud65c\uc6a9\ud558\uba74 \ud2b9\uc815 \ud0a4\uc6cc\ub4dc\uc5d0 \ub530\ub77c \uc704\ud0a4\ud53c\ub514\uc544 \ud398\uc774\uc9c0\ub97c \uac80\uc0c9\ud558\uace0, \ud544\uc694\ud55c \uc815\ubcf4\ub97c \uc27d\uac8c \uac00\uc838\uc62c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

3. \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac \uc124\uce58\ud558\uae30<\/h2>\n

\uc791\uc5c5\uc5d0 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud558\ub824\uba74 \uc544\ub798\uc758 \uba85\ub839\uc5b4\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. Hugging Face \ub77c\uc774\ube0c\ub7ec\ub9ac\uc640 Wikipedia API\ub97c \uc0ac\uc6a9\ud558\uae30 \uc704\ud574 transformers<\/code>\uc640 wikipedia-api<\/code> \ud328\ud0a4\uc9c0\ub97c \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n

pip install transformers wikipedia-api<\/code><\/pre>\n
4. Hugging Face \ubaa8\ub378 \uc120\ud0dd\ud558\uae30<\/h2>\n
\uc6b0\ub9ac\ub294 \ubb38\uc11c\uc758 \uad00\ub828\uc131\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud574 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud560 \uac83\uc785\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 distilbert-base-uncased<\/code> \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ubaa8\ub378\uc740 \ubcc0\ud615\ub41c BERT \ubaa8\ub378\uc785\ub2c8\ub2e4. \ubb38\uc11c\uc758 \uc784\ubca0\ub529\uc744 \uc5bb\uace0 \ub450 \ubb38\uc11c \uac04\uc758 \uc720\uc0ac\uc131\uc744 \uce21\uc815\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/p>\n
5. \ucf54\ub4dc \uc124\uba85<\/h2>\n
\uc774\uc81c \uc704\uc5d0\uc11c \uc124\uba85\ud55c \ub0b4\uc6a9\uc744 \ubc14\ud0d5\uc73c\ub85c Python \ucf54\ub4dc\ub97c \uc791\uc131\ud558\uaca0\uc2b5\ub2c8\ub2e4. \ucf54\ub4dc\uc758 \ub2e8\uacc4\ubcc4 \uc124\uba85\uc744 \ud3ec\ud568\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
5.1 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac \uc784\ud3ec\ud2b8<\/h3>\n
\nimport wikipediaapi\nfrom transformers import AutoTokenizer, AutoModel\nimport torch\n        <\/code><\/pre>\n
5.2 \ubaa8\ub378\uacfc \ud1a0\ud06c\ub098\uc774\uc800 \uc900\ube44<\/h3>\n
\uc774\uc81c \ubcc0\ud658\uae30\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uacfc \ud1a0\ud06c\ub098\uc774\uc800\ub97c \ucd08\uae30\ud654\ud569\ub2c8\ub2e4.<\/p>\n
\n# Hugging Face \ubaa8\ub378\uacfc \ud1a0\ud06c\ub098\uc774\uc800 \ucd08\uae30\ud654\nmodel_name = 'distilbert-base-uncased'\ntokenizer = AutoTokenizer.from_pretrained(model_name)\nmodel = AutoModel.from_pretrained(model_name)\n        <\/code><\/pre>\n
5.3 \uc704\ud0a4\ud53c\ub514\uc544 \uac80\uc0c9 \ud568\uc218 \uad6c\ud604<\/h3>\n
\uc704\ud0a4\ud53c\ub514\uc544\uc5d0\uc11c \ud0a4\uc6cc\ub4dc\ub97c \uac80\uc0c9\ud558\uace0, \uad00\ub828 \ubb38\uc11c\ub97c \ubc18\ud658\ud558\ub294 \ud568\uc218\ub97c \uc815\uc758\ud569\ub2c8\ub2e4.<\/p>\n
\ndef search_wikipedia(keyword):\n    wiki_wiki = wikipediaapi.Wikipedia('en')\n    page = wiki_wiki.page(keyword)\n    if page.exists():\n        return page.text\n    else:\n        return None\n        <\/code><\/pre>\n
5.4 \ubb38\uc11c\uc758 \uc784\ubca0\ub529 \uc0dd\uc131<\/h3>\n
\uac80\uc0c9\ub41c \ubb38\uc11c\uc758 \uc784\ubca0\ub529\uc744 \uc0dd\uc131\ud558\ub294 \ud568\uc218\ub97c \ub9cc\ub4ed\ub2c8\ub2e4.<\/p>\n
\ndef create_embedding(text):\n    inputs = tokenizer(text, return_tensors='pt', truncation=True, padding=True, max_length=512)\n    with torch.no_grad():\n        outputs = model(**inputs)\n    return outputs['last_hidden_state'].mean(dim=1)\n        <\/code><\/pre>\n
5.5 \ud0a4\uc6cc\ub4dc \uad00\ub828 \ubb38\uc11c \ucc3e\uae30<\/h3>\n
\uc8fc\uc5b4\uc9c4 \ud0a4\uc6cc\ub4dc\uc5d0 \ub300\ud574 \uad00\ub828 \uc815\ubcf4\uc640 \ube44\uc2b7\ud55c \ud398\uc774\uc9c0\ub97c \ucc3e\uae30 \uc704\ud574 \uc0dd\uc131\ud55c \uc784\ubca0\ub529\uc744 \ud65c\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n
\nkeyword = \"Deep Learning\"\nwiki_text = search_wikipedia(keyword)\n\nif wiki_text:\n    embedding = create_embedding(wiki_text)\n    print(\"\uc81c\ubaa9:\", keyword)\n    print(\"\ub0b4\uc6a9\uc758 \uc784\ubca0\ub529:\", embedding)\nelse:\n    print(\"\ud574\ub2f9 \ud0a4\uc6cc\ub4dc\uc5d0 \ub300\ud55c \uc704\ud0a4\ud53c\ub514\uc544 \ud398\uc774\uc9c0\ub97c \ucc3e\uc744 \uc218 \uc5c6\uc2b5\ub2c8\ub2e4.\")\n        <\/code><\/pre>\n
6. \ucf54\ub4dc \uc2e4\ud589 \ubc0f \uacb0\uacfc<\/h2>\n
\uc704\uc758 \ucf54\ub4dc\ub97c \uc2e4\ud589\ud558\uba74 \uc8fc\uc5b4\uc9c4 \ud0a4\uc6cc\ub4dc\uc5d0 \ub300\ud55c \uc704\ud0a4\ud53c\ub514\uc544 \ubb38\uc11c\uc758 \ub0b4\uc6a9\uacfc \uc784\ubca0\ub529\uc744 \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc784\ubca0\ub529\uc740 \ub098\uc911\uc5d0 \ub2e4\ub978 \ubb38\uc11c\uc640\uc758 \uc720\uc0ac\ub3c4\ub97c \uacc4\uc0b0\ud558\ub294 \ub370 \uc0ac\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
7. \uc720\uc0ac\ub3c4 \uacc4\uc0b0\ud558\uae30<\/h2>\n
\ucd94\uac00\uc801\uc73c\ub85c \ub2e4\ub978 \ubb38\uc11c\ub4e4\uacfc\uc758 \uc720\uc0ac\ub3c4\ub97c \uacc4\uc0b0\ud558\uc5ec, \uc785\ub825\ud55c \ud0a4\uc6cc\ub4dc\uc640 \uad00\ub828\ub41c \ub2e4\ub978 \uc8fc\uc81c\ub4e4\ub3c4 \ud0d0\uc0c9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc784\ubca0\ub529 \uac04\uc758 \ucf54\uc0ac\uc778 \uc720\uc0ac\ub3c4\ub97c \uacc4\uc0b0\ud558\uc5ec \uc720\uc0ac\ud55c \ubb38\uc11c\ub4e4\uc744 \uac80\uc0c9\ud574 \ubd05\uc2dc\ub2e4.<\/p>\n
\nfrom sklearn.metrics.pairwise import cosine_similarity\n\n# \uc784\ubca0\ub529\uc744 \ub450 \uac1c \uc0dd\uc131\ud55c \ud6c4, \uc720\uc0ac\ub3c4\ub97c \uacc4\uc0b0\ud569\ub2c8\ub2e4\nother_keyword = \"Machine Learning\"\nother_wiki_text = search_wikipedia(other_keyword)\n\nif other_wiki_text:\n    other_embedding = create_embedding(other_wiki_text)\n    similarity_score = cosine_similarity(embedding.numpy(), other_embedding.numpy())\n    print(f\"{keyword}\uc640 {other_keyword}\uc758 \uc720\uc0ac\ub3c4:\", similarity_score[0][0])\nelse:\n    print(\"\ud574\ub2f9 \ud0a4\uc6cc\ub4dc\uc5d0 \ub300\ud55c \uc704\ud0a4\ud53c\ub514\uc544 \ud398\uc774\uc9c0\ub97c \ucc3e\uc744 \uc218 \uc5c6\uc2b5\ub2c8\ub2e4.\")\n        <\/code><\/pre>\n
8. \uacb0\ub860<\/h2>\n
\uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\uc640 \uc704\ud0a4\ud53c\ub514\uc544 API\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud2b9\uc815 \ud0a4\uc6cc\ub4dc\uc5d0 \ub300\ud55c \uad00\ub828 \uc815\ubcf4\ub97c \uac80\uc0c9\ud558\uace0, \ud574\ub2f9 \ub0b4\uc6a9\uc758 \uc784\ubca0\ub529\uc744 \uc0dd\uc131\ud558\uc5ec \ub2e4\ub978 \ubb38\uc11c\uc640\uc758 \uc720\uc0ac\ub3c4\ub97c \ud3c9\uac00\ud558\ub294 \ubc29\ubc95\uc744 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \uc774\ub294 \uac80\uc0c9 \uc5d4\uc9c4 \uad6c\ucd95, \ucd94\ucc9c \uc2dc\uc2a4\ud15c, \uc815\ubcf4 \ucd94\ucd9c \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0 \uc751\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
9. \ub2e4\uc74c \ub2e8\uacc4<\/h2>\n
\uc774\uc81c \uc774 \uae30\ucd08\uc801\uc778 \uad6c\uc870\ub97c \ubc14\ud0d5\uc73c\ub85c \ucd94\uac00 \uae30\ub2a5\uc744 \uad6c\ud604\ud574 \ubcf4\uc2ed\uc2dc\uc624. \uc608\ub97c \ub4e4\uc5b4, \uc5ec\ub7ec \ubb38\uc11c \uac80\uc0c9 \ubc0f \ud074\ub7ec\uc2a4\ud130\ub9c1, \ub610\ub294 \uc0ac\uc6a9\uc790 \uc778\ud130\ud398\uc774\uc2a4\ub97c \ub9cc\ub4e4\uc5b4 \uc0ac\uc6a9\uc790\ub4e4\uc774 \uc27d\uac8c \ud0a4\uc6cc\ub4dc\ub97c \uac80\uc0c9\ud560 \uc218 \uc788\ub3c4\ub85d \ud558\ub294 \ubc29\ubc95\uc774 \uc788\uc2b5\ub2c8\ub2e4. Hugging Face\uc758 \ub2e4\uc591\ud55c \ubaa8\ub378\uacfc \uc704\ud0a4\ud53c\ub514\uc544 API\ub97c \ud65c\uc6a9\ud558\uc5ec \ub354 \ub9ce\uc740 \uae30\ub2a5\uc744 \uad6c\ud604\ud574 \ubcf4\uc138\uc694. <\/p>\n
10. \ucc38\uace0 \uc790\ub8cc<\/h2>\n
\n            – Hugging Face Transformers Documentation<\/a>
\n            – Wikipedia API Documentation<\/a>\n<\/p>\n<\/article>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub525\ub7ec\ub2dd\uacfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uac15\ub825\ud55c \ub3c4\uad6c\ub85c \uc790\ub9ac \uc7a1\uc558\uc2b5\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face Transformers\uc640 \ud568\uaed8 Wikipedia API\ub97c \ud65c\uc6a9\ud558\uc5ec \uc8fc\uc5b4\uc9c4 \ud0a4\uc6cc\ub4dc\ub85c \uc704\ud0a4\ud53c\ub514\uc544\uc5d0\uc11c \uc801\uc808\ud55c \ubb38\uc11c\ub97c \uac80\uc0c9\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. 1. Hugging Face Transformers\ub780? Hugging Face\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc758 \ud559\uc2b5, \ucd94\ub860 \ubc0f \ubc30\ud3ec\ub97c \uc704\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc81c\uacf5\ud558\ub294 \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4. Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \uc27d\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\uac8c … \ub354 \ubcf4\uae30 “\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc704\ud0a4\ud53c\ub514\uc544 \uc601\ubb38 \ud0a4\uc6cc\ub4dc \uac80\uc0c9”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[30],"tags":[],"class_list":["post-29678","post","type-post","status-publish","format-standard","hentry","category-30"],"yoast_head":"\n\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc704\ud0a4\ud53c\ub514\uc544 \uc601\ubb38 \ud0a4\uc6cc\ub4dc \uac80\uc0c9 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/29678\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc704\ud0a4\ud53c\ub514\uc544 \uc601\ubb38 \ud0a4\uc6cc\ub4dc \uac80\uc0c9 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ub525\ub7ec\ub2dd\uacfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uac15\ub825\ud55c \ub3c4\uad6c\ub85c \uc790\ub9ac \uc7a1\uc558\uc2b5\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face Transformers\uc640 \ud568\uaed8 Wikipedia API\ub97c \ud65c\uc6a9\ud558\uc5ec \uc8fc\uc5b4\uc9c4 \ud0a4\uc6cc\ub4dc\ub85c \uc704\ud0a4\ud53c\ub514\uc544\uc5d0\uc11c \uc801\uc808\ud55c \ubb38\uc11c\ub97c \uac80\uc0c9\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. 1. Hugging Face Transformers\ub780? Hugging Face\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc758 \ud559\uc2b5, \ucd94\ub860 \ubc0f \ubc30\ud3ec\ub97c \uc704\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc81c\uacf5\ud558\ub294 \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4. 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