\n1. \uc11c\ub860<\/h2>\n
\n \ud604\ub300\uc758 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \uc804\uc774 \ud559\uc2b5(Transfer Learning)\uacfc \uc0ac\uc804 \ud6c8\ub828(pre-training) \ubaa8\ub378\uc774 \ud070 \uc778\uae30\ub97c \ub04c\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc774\ub7ec\ud55c \ubaa8\ub378\uc744 \uc27d\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ub3c4\uad6c\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec DistilGPT2 \ubaa8\ub378\uc744 \uc124\uce58\ud558\uace0, \uc0ac\uc804 \ud559\uc2b5\ub41c \ubaa8\ub378\uc744 \ubd88\ub7ec\uc624\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4.\n <\/p>\n<\/section>\n\n2. DistilGPT2\ub780 \ubb34\uc5c7\uc778\uac00?<\/h2>\n
\n DistilGPT2\ub294 OpenAI\uc758 GPT-2 \ubaa8\ub378\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \uacbd\ub7c9\ud654 \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc778 GPT-2 \ubaa8\ub378\ubcf4\ub2e4 \ud6e8\uc52c \uc801\uc740 \uc218\uc758 \ud30c\ub77c\ubbf8\ud130\ub97c \uac00\uc9c0\uace0 \uc788\uc9c0\ub9cc, \uc131\ub2a5\uc740 \uaf64 \uc720\uc9c0\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \ud6c8\ub828 \uc2dc\uac04\uacfc \ub9ac\uc18c\uc2a4\ub97c \uc904\uc774\ub294 \ub370 \uc720\ub9ac\ud558\uc5ec \uc2e4\uc6a9\uc801\uc778 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0\uc11c \ub9ce\uc774 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.\n <\/p>\n
\n- \uacbd\ub7c9\uc131:<\/strong> DistilGPT2\ub294 \uc218\ubc31\ub9cc \uac1c\uc758 \ud30c\ub77c\ubbf8\ud130\ub97c \uac10\ucd95\ud558\uc5ec \ub354 \ube60\ub978 \ucc98\ub9ac \uc18d\ub3c4\ub97c \uc790\ub791\ud569\ub2c8\ub2e4.<\/li>\n
- \uc6b0\uc218\ud55c \uc131\ub2a5:<\/strong> \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc774\ubbc0\ub85c \ubc94\uc6a9\uc801\uc778 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \uc791\uc5c5\uc5d0 \uc798 \ub9de\uc2b5\ub2c8\ub2e4.<\/li>\n
- \ub2e4\uc591\ud55c \ud65c\uc6a9:<\/strong> \ud14d\uc2a4\ud2b8 \uc0dd\uc131, \uc694\uc57d, \ubc88\uc5ed \ub4f1 \uc5ec\ub7ec NLP \ud0dc\uc2a4\ud06c\uc5d0 \uc0ac\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/section>\n\n
3. \uc124\uce58\ud558\uae30<\/h2>\n
\n Hugging Face\uc758 Transformers\uc640 PyTorch \ub610\ub294 TensorFlow \ub77c\uc774\ube0c\ub7ec\ub9ac\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \uac00\uc7a5 \uac04\ub2e8\ud558\uac8c\ub294 pip\ub97c \uc774\uc6a9\ud558\uc5ec \uc124\uce58\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798\uc758 \uba85\ub839\uc5b4\ub97c \uc0ac\uc6a9\ud574\ubcf4\uc138\uc694.\n <\/p>\n
\npip install transformers torch<\/code>\n <\/pre>\n<\/section>\n\n4. \uc0ac\uc804 \ud559\uc2b5 \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30<\/h2>\n
\n \uc124\uce58\uac00 \uc644\ub8cc\ub418\uba74, \uc0ac\uc804 \ud6c8\ub828\ub41c DistilGPT2 \ubaa8\ub378\uc744 \ubd88\ub7ec\uc62c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798\uc758 \uc608\uc81c \ucf54\ub4dc\ub97c \ud1b5\ud574 \uc774\ub97c \uc218\ud589\ud558\uaca0\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n\nfrom transformers import DistilGPT2Tokenizer, DistilGPT2LMHeadModel\n\n# 1. \ud1a0\ud06c\ub098\uc774\uc800\uc640 \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30\ntokenizer = DistilGPT2Tokenizer.from_pretrained(\"distilgpt2\")\nmodel = DistilGPT2LMHeadModel.from_pretrained(\"distilgpt2\")\n\n# 2. \ud14d\uc2a4\ud2b8 \uc785\ub825\ninput_text = \"AI\ub294 \ubbf8\ub798\uc758 \uae30\uc220\uc785\ub2c8\ub2e4.\"\ninput_ids = tokenizer.encode(input_text, return_tensors='pt')\n\n# 3. \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud55c \ud14d\uc2a4\ud2b8 \uc0dd\uc131\noutput = model.generate(input_ids, max_length=50, num_return_sequences=1)\n\n# 4. \uc0dd\uc131\ub41c \ud14d\uc2a4\ud2b8 \ucd9c\ub825\ngenerated_text = tokenizer.decode(output[0], skip_special_tokens=True)\nprint(generated_text)\n<\/code>\n <\/pre>\n\n \uc704 \ucf54\ub4dc\ub294 DistilGPT2 \ubaa8\ub378\uc744 \ubd88\ub7ec\uc640 \uc785\ub825\ub41c \ud14d\uc2a4\ud2b8\ub97c \uae30\ubc18\uc73c\ub85c \ud574\uc11c \uc0c8\ub85c\uc6b4 \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4.\n <\/p>\n<\/section>\n\n5. \ucf54\ub4dc \ubd84\uc11d<\/h2>\n
1. \ud1a0\ud06c\ub098\uc774\uc800\uc640 \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30:<\/strong><\/p>\n\nDistilGPT2Tokenizer.from_pretrained(\"distilgpt2\")<\/code>\uc640 DistilGPT2LMHeadModel.from_pretrained(\"distilgpt2\")<\/code>\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc0ac\uc804 \ud559\uc2b5\ub41c \ud1a0\ud06c\ub098\uc774\uc800\uc640 \ubaa8\ub378\uc744 \ubd88\ub7ec\uc635\ub2c8\ub2e4.\n <\/p>\n2. \ud14d\uc2a4\ud2b8 \uc785\ub825:<\/strong><\/p>\n\n \uc785\ub825 \ud14d\uc2a4\ud2b8\ub97c tokenizer.encode()<\/code>\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud1a0\ud070\ud654\ud569\ub2c8\ub2e4. return_tensors='pt'<\/code> \uc778\uc790\ub294 PyTorch \ud150\uc11c \ud615\ud0dc\ub85c \ubc18\ud658\ud558\ub3c4\ub85d \ud574\uc90d\ub2c8\ub2e4.\n <\/p>\n3. \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud55c \ud14d\uc2a4\ud2b8 \uc0dd\uc131:<\/strong><\/p>\n\nmodel.generate()<\/code> \uba54\uc18c\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc785\ub825\ub41c \ud14d\uc2a4\ud2b8\ub85c\ubd80\ud130 \ucd5c\ub300 50\uac1c\uc758 \ub2e8\uc5b4\ub85c \uc774\ub8e8\uc5b4\uc9c4 \uc0c8\ub85c\uc6b4 \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4.\n <\/p>\n4. \uc0dd\uc131\ub41c \ud14d\uc2a4\ud2b8 \ucd9c\ub825:<\/strong><\/p>\n\ntokenizer.decode()<\/code>\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc0dd\uc131\ub41c \uc544\uc774\ub514\ub97c \ub2e4\uc2dc \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4. \ub610\ud55c skip_special_tokens=True<\/code>\ub97c \ud1b5\ud574 \ud2b9\uc218 \ud1a0\ud070\uc740 \uc81c\uc678\ud569\ub2c8\ub2e4.\n <\/p>\n<\/section>\n\n6. \ud65c\uc6a9 \uc608\uc81c<\/h2>\n
\n \uc2e4\uc81c \ud658\uacbd\uc5d0\uc11c DistilGPT2 \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\ub294 \ub2e4\uc591\ud55c \uc608\uc81c\uc5d0 \ub300\ud574 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \ud14d\uc2a4\ud2b8 \uc0dd\uc131, \ub300\ud654\ud615 AI, \ud14d\uc2a4\ud2b8 \uc694\uc57d \ub4f1 \uc5ec\ub7ec \uc0c1\ud669\uc5d0\uc11c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
6.1 \ud14d\uc2a4\ud2b8 \uc0dd\uc131 \ubaa8\ub378<\/h3>\n
\n \ud2b9\uc815 \uc8fc\uc81c\ub098 \ud0a4\uc6cc\ub4dc\uc5d0 \uae30\ubc18\ud55c \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud558\ub294 \ud14d\uc2a4\ud2b8 \uc0dd\uc131 \ubaa8\ub378\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n\ndef generate_text(model, tokenizer, prompt, max_length=50):\n input_ids = tokenizer.encode(prompt, return_tensors='pt')\n output = model.generate(input_ids, max_length=max_length, num_return_sequences=1)\n return tokenizer.decode(output[0], skip_special_tokens=True)\n\nprompt = \"\ub525\ub7ec\ub2dd\uc740\"\ngenerated = generate_text(model, tokenizer, prompt)\nprint(generated)\n<\/code>\n <\/pre>\n\n \uc704\uc758 \ud568\uc218\ub294 \uc8fc\uc5b4\uc9c4 \ud504\ub86c\ud504\ud2b8\ub97c \ubc14\ud0d5\uc73c\ub85c \uc0c8 \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud574\uc8fc\ub294 \uae30\ub2a5\uc744 \uac00\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
6.2 \ub300\ud654\ud615 AI \uc608\uc81c<\/h3>\n
\n \uc0ac\uc6a9\uc790\uc640 \ub300\ud654\ud558\ub294 \uac04\ub2e8\ud55c AI\ub3c4 \uad6c\ud604\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n\ndef chat_with_ai(model, tokenizer):\n print(\"AI\uc640 \ub300\ud654\ub97c \uc2dc\uc791\ud569\ub2c8\ub2e4. \uc885\ub8cc\ud558\ub824\uba74 'quit'\ub97c \uc785\ub825\ud558\uc138\uc694.\")\n while True:\n user_input = input(\"\ub2f9\uc2e0: \")\n if user_input.lower() == 'quit':\n break\n response = generate_text(model, tokenizer, user_input)\n print(\"AI: \", response)\n\nchat_with_ai(model, tokenizer)\n<\/code>\n <\/pre>\n<\/section>\n\n7. \ubaa8\ub378 \ud3c9\uac00 \ubc0f \ud29c\ub2dd<\/h2>\n
\n \uc0ac\uc804\ud559\uc2b5\ub41c \ubaa8\ub378\uc744 \uc561\uc138\uc2a4\ud558\uace0 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ubc29\ubc95\uc744 \ubc30\uc6e0\uc9c0\ub9cc, \ud2b9\uc815 \ub3c4\uba54\uc778\uc5d0 \ub9de\ucdb0 \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0a4\uae30 \uc704\ud574 \ubaa8\ub378\uc744 \ubbf8\uc138 \uc870\uc815\ud560 \ud544\uc694\uac00 \uc788\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Fine-tuning\uc744 \ud1b5\ud574 \ud2b9\uc815 \ub370\uc774\ud130\uc14b\uc5d0 \ub300\ud574 \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0ac \uc218 \uc788\uc73c\uba70, Hugging Face\uc758 Trainer<\/code> \ud074\ub798\uc2a4\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc190\uc27d\uac8c \uc774 \uc791\uc5c5\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n\n\nfrom transformers import Trainer, TrainingArguments\n\n# \ud2b8\ub808\uc774\ub2dd \uc544\uaddc\uba3c\ud2b8 \uc124\uc815\ntraining_args = TrainingArguments(\n output_dir='.\/results',\n num_train_epochs=3,\n per_device_train_batch_size=2,\n save_steps=10_000,\n save_total_limit=2,\n)\n\n# Trainer \uc778\uc2a4\ud134\uc2a4 \uc0dd\uc131\ntrainer = Trainer(\n model=model,\n args=training_args,\n train_dataset=your_train_dataset,\n)\n\n# \ubaa8\ub378 \ud559\uc2b5\ntrainer.train()\n<\/code>\n <\/pre>\n<\/section>\n\n8. \uacb0\ub860<\/h2>\n
\n \ubcf8 \uac15\uc88c\ub97c \ud1b5\ud574 Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec DistilGPT2 \ubaa8\ub378\uc744 \uc124\uce58\ud558\uace0 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ubd88\ub7ec\uc624\ub294 \ubc29\ubc95\uc744 \ubc30\uc6e0\uc2b5\ub2c8\ub2e4. \ud14d\uc2a4\ud2b8 \uc0dd\uc131, \ub300\ud654\ud615 AI \ub4f1 \uc5ec\ub7ec \uc751\uc6a9 \ud504\ub85c\uadf8\ub7a8\uc744 \ub9cc\ub4e4\uc5b4\ubcfc \uc218 \uc788\uc73c\uba70, \ub354 \ub098\uc544\uac00 Fine-tuning\uc744 \ud1b5\ud574 \ud2b9\uc815 \ub370\uc774\ud130\uc14b\uc5d0 \ub9de\ucdb0 \ubaa8\ub378\uc744 \uac1c\uc120\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n<\/section>\n<\/article>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
1. \uc11c\ub860 \ud604\ub300\uc758 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \uc804\uc774 \ud559\uc2b5(Transfer Learning)\uacfc \uc0ac\uc804 \ud6c8\ub828(pre-training) \ubaa8\ub378\uc774 \ud070 \uc778\uae30\ub97c \ub04c\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc774\ub7ec\ud55c \ubaa8\ub378\uc744 \uc27d\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ub3c4\uad6c\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec DistilGPT2 \ubaa8\ub378\uc744 \uc124\uce58\ud558\uace0, \uc0ac\uc804 \ud559\uc2b5\ub41c \ubaa8\ub378\uc744 \ubd88\ub7ec\uc624\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. 2. DistilGPT2\ub780 \ubb34\uc5c7\uc778\uac00? DistilGPT2\ub294 OpenAI\uc758 GPT-2 \ubaa8\ub378\uc744 \uae30\ubc18\uc73c\ub85c \ud55c … \ub354 \ubcf4\uae30 “\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, DistilGPT2 \ub77c\uc774\ube0c\ub7ec\ub9ac \uc124\uce58 \ubc0f \uc0ac\uc804\ud559\uc2b5 \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30”<\/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-29588","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, DistilGPT2 \ub77c\uc774\ube0c\ub7ec\ub9ac \uc124\uce58 \ubc0f \uc0ac\uc804\ud559\uc2b5 \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30 - \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\/29588\/\" \/>\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, DistilGPT2 \ub77c\uc774\ube0c\ub7ec\ub9ac \uc124\uce58 \ubc0f \uc0ac\uc804\ud559\uc2b5 \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"1. \uc11c\ub860 \ud604\ub300\uc758 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \uc804\uc774 \ud559\uc2b5(Transfer Learning)\uacfc \uc0ac\uc804 \ud6c8\ub828(pre-training) \ubaa8\ub378\uc774 \ud070 \uc778\uae30\ub97c \ub04c\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc774\ub7ec\ud55c \ubaa8\ub378\uc744 \uc27d\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ub3c4\uad6c\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec DistilGPT2 \ubaa8\ub378\uc744 \uc124\uce58\ud558\uace0, \uc0ac\uc804 \ud559\uc2b5\ub41c \ubaa8\ub378\uc744 \ubd88\ub7ec\uc624\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. 2. DistilGPT2\ub780 \ubb34\uc5c7\uc778\uac00? 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