\ucd5c\uadfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \ub525\ub7ec\ub2dd \ubaa8\ub378\uc758 \ubc1c\uc804\uc774 \ub208\ubd80\uc2e0 \uc18d\ub3c4\ub85c \uc774\ub8e8\uc5b4\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \ud5c8\uae45\ud398\uc774\uc2a4(Hugging Face)<\/strong>\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc774\ub7ec\ud55c \ubc1c\uc804\uc744 \uc774\ub044\ub294 \uc8fc\uc694 \ub3c4\uad6c \uc911 \ud558\ub098\ub85c \uc790\ub9ac \uc7a1\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4\uc758 \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubc0f \uad00\ub828 \ud0dc\uc2a4\ud06c\ub97c \uc704\ud55c \uc5ec\ub7ec \ucd5c\ucca8\ub2e8 \ubaa8\ub378\uc744 \uc27d\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub3c4\ub85d \ud574\uc8fc\ub294 \ud30c\uc774\uc36c \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\ub294 \ud14d\uc2a4\ud2b8 \uc0dd\uc131, \uc9c8\ubb38 \ub2f5\ubcc0, \uc694\uc57d \ubc0f \ub2e4\uc591\ud55c \uc5b8\uc5b4 \ubaa8\ub378\ub9c1 \uc791\uc5c5\uc5d0 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ub2e4\uc591\ud55c \uc0ac\uc804 \ud6c8\ub828 \ubaa8\ub378(Pretrained Models)\uc774 \ud3ec\ud568\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n GPT-Neo<\/strong>\ub294 EleutherAI\uac00 \uac1c\ubc1c\ud55c \uc624\ud508 \uc18c\uc2a4 \uc5b8\uc5b4 \uc0dd\uc131 \ubaa8\ub378\uc785\ub2c8\ub2e4. GPT-3\uc640 \uc720\uc0ac\ud55c \uad6c\uc870\ub97c \uac00\uc9c4 \uc774 \ubaa8\ub378\uc740 \ub2e4\uc591\ud55c NLP \ud0dc\uc2a4\ud06c\uc5d0 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc73c\uba70, \uadf8 \uc911\uc5d0\uc11c\ub3c4 \ud14d\uc2a4\ud2b8 \uc0dd\uc131 \uc791\uc5c5\uc5d0 \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubcf4\uc785\ub2c8\ub2e4. GPT-Neo\ub294 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \uc544\ud0a4\ud14d\ucc98\ub97c \uae30\ubc18\uc73c\ub85c \ud558\uba70, \ub2e4\uc74c \ub2e8\uc5b4\ub97c \uc608\uce21\ud558\ub294 \ubc29\uc2dd\uc73c\ub85c \uc791\ub3d9\ud569\ub2c8\ub2e4.<\/p>\n \ud1a0\ud06c\ub098\uc774\uc800(Tokenization)\ub294 \ud14d\uc2a4\ud2b8\ub97c \ubaa8\ub378\uc774 \uc774\ud574\ud560 \uc218 \uc788\ub294 \ud615\uc2dd\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4. GPT-Neo\uc758 \ud1a0\ud06c\ub098\uc774\uc800\ub294 \uc785\ub825 \ud14d\uc2a4\ud2b8\ub97c \uac1c\ubcc4 \ub2e8\uc5b4 \ub610\ub294 \uc11c\ube0c\uc6cc\ub4dc(Subword)\ub85c \ubd84\ud560\ud558\uace0, \uc774\ub97c \uc815\uc218 \uc778\ub371\uc2a4\uc758 \ubc30\uc5f4\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4. \uc774\ub807\uac8c \ubcc0\ud658\ub41c \uc778\ub371\uc2a4\ub294 \ubaa8\ub378\uc5d0 \ub300\ud55c \uc785\ub825\uc73c\ub85c \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/p>\n \ud1a0\ud06c\ub098\uc774\uc9d5\uc740 \uc6d0\ud558\ub294 \uacb0\uacfc\ub97c \uc5bb\uae30 \uc704\ud574 \ud544\uc218\uc801\uc778 \ub2e8\uacc4\uc785\ub2c8\ub2e4. \uc801\uc808\ud55c \ud1a0\ud06c\ub098\uc774\uc9d5\uc744 \ud1b5\ud574 \ubaa8\ub378\uc774 \uc785\ub825\uc744 \ubcf4\ub2e4 \uc798 \uc774\ud574\ud558\uace0, \uc131\ub2a5\uc744 \uadf9\ub300\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. GPT-Neo \ubaa8\ub378\uc5d0\uc11c\ub294 Byte-Pair Encoding(BPE) \ubc29\uc2dd\uc744 \ud1b5\ud574 \uc11c\ube0c\uc6cc\ub4dc \ud1a0\ud070\ud654\ub97c \uc9c4\ud589\ud569\ub2c8\ub2e4.<\/p>\n \ubcf8 \uac15\uc88c\ub97c \uc9c4\ud589\ud558\uae30 \uc704\ud574\uc11c\ub294 Python\uacfc \ud568\uaed8 \uc544\ub798 \uc608\uc81c \ucf54\ub4dc\ub294 GPT-Neo \ubaa8\ub378\uc744 \ub85c\ub4dc\ud558\uace0, \ud1a0\ud06c\ub098\uc774\uc800\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud14d\uc2a4\ud2b8\ub97c \ud1a0\ud06c\ub098\uc774\uc9d5\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/p>\n \uc704 \ucf54\ub4dc\ub97c \uc2e4\ud589\ud558\uba74 \ub2e4\uc74c\uacfc \uac19\uc740 \ucd9c\ub825 \uacb0\uacfc\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec GPT-Neo \ubaa8\ub378\uc758 \ud1a0\ud06c\ub098\uc774\uc9d5 \uacfc\uc815\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ud1a0\ud06c\ub098\uc774\uc9d5\uc740 NLP \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \uc88c\uc6b0\ud558\ub294 \uc911\uc694\ud55c \uc694\uc18c\uc774\uba70, \uc801\uc808\ud55c \ud1a0\ud06c\ub098\uc774\uc800\uc758 \uc0ac\uc6a9\uc774 \ud544\uc218\uc801\uc785\ub2c8\ub2e4.<\/p>\n \ub2e4\uc74c \ub2e8\uacc4\ub85c\ub294 \uc774\ub807\uac8c \ud1a0\ud06c\ub098\uc774\uc9d5 \ub41c \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc2e4\uc81c \ud14d\uc2a4\ud2b8 \uc0dd\uc131 \ud0dc\uc2a4\ud06c\ub97c \uc218\ud589\ud558\ub294 \uac83\uc744 \ucd94\ucc9c\ub4dc\ub9bd\ub2c8\ub2e4. \ucd94\uac00\uc801\uc73c\ub85c, \ub2e4\uc591\ud55c \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\ub4e4\uc744 \uc870\uc815\ud574\ubcf4\uba70 \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \uadf9\ub300\ud654\ud558\ub294 \ubc29\ubc95\uc744 \uace0\ubbfc\ud574 \ubcf4\uae38 \ubc14\ub78d\ub2c8\ub2e4.<\/p>\n <\/body><\/p>\n","protected":false},"excerpt":{"rendered":"transformers<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec GPT-Neo<\/strong> \ubaa8\ub378\uc758 \ud1a0\ud06c\ub098\uc774\uc9d5\uc5d0 \ub300\ud574 \uc2ec\ub3c4 \uc788\uac8c \ud0d0\uad6c\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub780?<\/h2>\n
2. GPT-Neo\ub780?<\/h2>\n
3. GPT-Neo\uc758 \ud1a0\ud06c\ub098\uc774\uc9d5<\/h2>\n
3.1 \ud1a0\ud06c\ub098\uc774\uc9d5\uc758 \uc911\uc694\uc131<\/h3>\n
4. \ud658\uacbd \uc124\uc815<\/h2>\n
transformers<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4. \ub2e4\uc74c\uacfc \uac19\uc740 \uba85\ub839\uc5b4\ub85c \uc124\uce58\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\npip install transformers<\/code><\/pre>\n5. \ud30c\uc774\uc36c \uc608\uc81c \ucf54\ub4dc<\/h2>\n
from transformers import GPTNeoTokenizer\n\n# \ud1a0\ud06c\ub098\uc774\uc800 \ub85c\ub4dc\ntokenizer = GPTNeoTokenizer.from_pretrained(\"EleutherAI\/gpt-neo-125M\")\n\n# \ud1a0\ud06c\ub098\uc774\uc9d5\ud560 \ud14d\uc2a4\ud2b8\ntext = \"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub97c \ud1b5\ud574 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uc27d\uac8c \ub2e4\ub8f0 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\"\n\n# \ud14d\uc2a4\ud2b8\ub97c \ud1a0\ud070\uc73c\ub85c \ubcc0\ud658\ntokens = tokenizer.tokenize(text)\nprint(\"\ud1a0\ud070:\", tokens)\n\n# \ud1a0\ud070\uc744 ID\ub85c \ubcc0\ud658\ntoken_ids = tokenizer.convert_tokens_to_ids(tokens)\nprint(\"\ud1a0\ud070 ID:\", token_ids)<\/code><\/pre>\n5.1 \ucf54\ub4dc \uc124\uba85<\/h3>\n
\n
from transformers import GPTNeoTokenizer<\/code>: \ud5c8\uae45\ud398\uc774\uc2a4\uc758 GPT-Neo \ud1a0\ud06c\ub098\uc774\uc800\ub97c \uac00\uc838\uc635\ub2c8\ub2e4.<\/li>\ntokenizer = GPTNeoTokenizer.from_pretrained(\"EleutherAI\/gpt-neo-125M\")<\/code>: \uc0ac\uc804 \ud6c8\ub828\ub41c GPT-Neo \ud1a0\ud06c\ub098\uc774\uc800\ub97c \ub85c\ub4dc\ud569\ub2c8\ub2e4.<\/li>\ntext<\/code>: \ud1a0\ud06c\ub098\uc774\uc9d5\ud560 \ud14d\uc2a4\ud2b8\ub97c \uc815\uc758\ud569\ub2c8\ub2e4.<\/li>\ntokenize(text)<\/code>: \uc785\ub825 \ud14d\uc2a4\ud2b8\ub97c \ud1a0\ud070\ud654\ud569\ub2c8\ub2e4.<\/li>\nconvert_tokens_to_ids(tokens)<\/code>: \ud1a0\ud070\uc744 \ubaa8\ub378 \uc785\ub825\uc5d0 \uc801\ud569\ud55c \uc815\uc218 ID\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n6. \uc608\uc81c \uc2e4\ud589 \uacb0\uacfc<\/h2>\n
\ud1a0\ud070: ['\ud5c8', '\uae45', '\ud398', '\uc774\uc2a4', ' ', '\ud2b8', '\ub79c', '\uc2a4', '\ud3ec', '\uba38', '\ub97c', ' ', '\ud1b5', '\ud574', ' ', '\ub525', '\ub7ec\ub2dd', ' ', '\ubaa8\ub378', '\uc744', ' ', '\uc26c', '\uc6b4', '\ud558', '\uac8c', ' ', '\ub2e4', '\ub8e8', '\ub97c', ' ', '\uc218', ' ', '\uc788', '\uc2b5\ub2c8\ub2e4', '.']\n\ud1a0\ud070 ID: [655, 2841, 1344, 2758, 6, 818, 442, 1878, 2065, 2337, 3094, 6, 1032, 602, 6, 3301, 1130, 2755, 2931, 6, 840, 2855, 14052, 149, 600, 851, 334, 1352, 920, 6]\n<\/code><\/pre>\n7. \uacb0\ub860 \ubc0f \ub2e4\uc74c \ub2e8\uacc4<\/h2>\n