{"id":29694,"date":"2024-10-28T01:56:07","date_gmt":"2024-10-28T01:56:07","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=29694"},"modified":"2024-11-26T06:51:42","modified_gmt":"2024-11-26T06:51:42","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%bd%94%eb%9e%a9%ec%97%90%ec%84%9c-%ec%98%a4%eb%94%94%ec%98%a4","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/29694\/","title":{"rendered":"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \ucf54\ub7a9\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130 \ud655\uc778"},"content":{"rendered":"<p><body><\/p>\n<p>\n        \ucd5c\uadfc \uc778\uacf5\uc9c0\ub2a5(AI) \ubc0f \uae30\uacc4\ud559\uc2b5(ML) \ubd84\uc57c\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \ud65c\uc6a9\ub3c4\uac00 \uc0c1\uc2b9\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \ud5c8\uae45\ud398\uc774\uc2a4(Hugging Face)\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 \ud2b8\ub80c\uc2a4\ud3ec\uba38(transformer) \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \ud070 \uc778\uae30\ub97c \ub04c\uace0 \uc788\uc73c\uba70, \uc624\ub514\uc624 \ub370\uc774\ud130 \ucc98\ub9ac \ubc0f \ubcc0\ud658\uc5d0\ub3c4 \ud65c\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<h2>1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \uc18c\uac1c<\/h2>\n<p>\n        \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub2e4\uc591\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\uba70, \ucee4\uc2a4\ud130\ub9c8\uc774\uc988\uc640 \uac04\ud3b8\ud55c \ud65c\uc6a9\uc774 \ud2b9\uc9d5\uc785\ub2c8\ub2e4. \uc0ac\uc6a9\uc790\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ub2e4\uc6b4\ub85c\ub4dc\ud558\uc5ec \uc190\uc27d\uac8c \uac01\uc885 NLP \ubc0f \uc624\ub514\uc624 \uad00\ub828 \uc791\uc5c5\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \uac01\uc885 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \uae30\uacc4\ud559\uc2b5 \ud504\ub85c\uc138\uc2a4\ub97c \uac04\uc18c\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<h2>2. \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \uc774\ud574<\/h2>\n<p>\n        \uc624\ub514\uc624 \ub370\uc774\ud130\ub294 \uc18c\ub9ac\uc758 \ud30c\ud615\uc744 \ub514\uc9c0\ud138\ud654\ud55c \uac83\uc774\uba70, \uc8fc\ub85c WAV, MP3, FLAC \ub4f1\uc758 \ud615\uc2dd\uc73c\ub85c \uc800\uc7a5\ub429\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c \uc624\ub514\uc624 \ub370\uc774\ud130\ub294 \uc2dc\uac04\uc5d0 \ub530\ub77c \uc5f0\uc18d\uc801\uc778 \ud30c\ud615\uc744 \uac00\uc9c0\uace0 \uc788\uc5b4, \uc774\ub97c \ubd84\uc11d\ud558\uae30 \uc704\ud574 \uac01\uc885 \uc2e0\ud638 \ucc98\ub9ac \uae30\ubc95\uc774 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \ub525\ub7ec\ub2dd \ubaa8\ub378\uc740 \uc774\ub7ec\ud55c \uc624\ub514\uc624 \ub370\uc774\ud130\ub97c \uc785\ub825\uc73c\ub85c \ubc1b\uc544 \ub2e4\uc591\ud55c \uc791\uc5c5\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<h3>2.1 \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \ud2b9\uc9d5<\/h3>\n<ul>\n<li><strong>Sampling Rate:<\/strong> \uc624\ub514\uc624 \uc2e0\ud638\uac00 \ucd08\ub2f9 \uc0d8\ud50c\ub9c1\ub418\ub294 \ud69f\uc218\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>Duration:<\/strong> \uc624\ub514\uc624\uc758 \uae38\uc774, \uc989 \uc7ac\uc0dd \uc2dc\uac04\uc774 \ub429\ub2c8\ub2e4.<\/li>\n<li><strong>Channels:<\/strong> \uc624\ub514\uc624\uc758 \ucc44\ub110 \uc218\ub85c, \ubaa8\ub178, \uc2a4\ud14c\ub808\uc624 \ub4f1 \ub2e4\uc591\ud55c \ud615\ud0dc\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h2>3. Google Colab\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130 \ud655\uc778\ud558\uae30<\/h2>\n<p>\n        \uc774\uc81c Google Colab \ud658\uacbd\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130\ub97c \ud655\uc778\ud558\ub294 \uacfc\uc815\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. Google Colab\uc740 \ud074\ub77c\uc6b0\ub4dc \uae30\ubc18\uc758 Jupyter \ub178\ud2b8\ubd81 \ud658\uacbd\uc73c\ub85c, Python \ucf54\ub4dc\ub97c \uc27d\uac8c \uc2e4\ud589\ud560 \uc218 \uc788\ub294 \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4.\n    <\/p>\n<h3>3.1 Google Colab \ud658\uacbd \uc124\uc815<\/h3>\n<p>\n        \uba3c\uc800 Google Colab\uc5d0 \uc811\uc18d\ud558\uace0 \uc0c8\ub85c\uc6b4 Python 3 \ub178\ud2b8\ubd81\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4. \uadf8\ub7f0 \ub2e4\uc74c, \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4.\n    <\/p>\n<pre><code>!pip install transformers datasets soundfile<\/code><\/pre>\n<h3>3.2 \uc624\ub514\uc624 \ub370\uc774\ud130 \ub85c\ub4dc \ubc0f \ud655\uc778<\/h3>\n<p>\n        \uc774\uc81c \uc624\ub514\uc624 \ub370\uc774\ud130\ub97c\ub85c\ub4dc\ud558\uace0 \ud655\uc778\ud558\ub294 \ucf54\ub4dc\ub97c \uc791\uc131\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<br \/>\n        \ud5c8\uae45\ud398\uc774\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc624\ub514\uc624 \ub370\uc774\ud130\ub97c \uc27d\uac8c \ub85c\ub4dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<pre><code>import torch\nfrom transformers import Wav2Vec2ForCTC, Wav2Vec2Tokenizer\nfrom datasets import load_dataset\n\n# \ub370\uc774\ud130\uc14b \ub85c\ub4dc\ndataset = load_dataset(\"superb\", split=\"validation\")\naudio_file = dataset[0][\"audio\"][\"array\"]\n\n# \ubaa8\ub378 \ub85c\ub4dc\ntokenizer = Wav2Vec2Tokenizer.from_pretrained(\"facebook\/wav2vec2-base-960h\")\nmodel = Wav2Vec2ForCTC.from_pretrained(\"facebook\/wav2vec2-base-960h\")\n\n# \uc624\ub514\uc624 \ub370\uc774\ud130 \uae38\uc774 \ud655\uc778\nprint(f\"Audio length: {len(audio_file) \/ 16000} seconds\")\n<\/code><\/pre>\n<h4>\uc704 \ucf54\ub4dc \uc124\uba85:<\/h4>\n<ul>\n<li>\ud5c8\uae45\ud398\uc774\uc2a4\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 <code>Wav2Vec2ForCTC<\/code> \ubaa8\ub378\uacfc <code>Wav2Vec2Tokenizer<\/code> \ub97c \uc784\ud3ec\ud2b8\ud569\ub2c8\ub2e4.<\/li>\n<li>\uc624\ub514\uc624 \ub370\uc774\ud130\uc14b\uc744 \ub85c\ub4dc\ud558\uace0, \uccab \ubc88\uc9f8 \uc624\ub514\uc624 \ud30c\uc77c\uc744 \ubc30\uc5f4\ub85c \uac00\uc838\uc635\ub2c8\ub2e4.<\/li>\n<li>\ubaa8\ub378\uc744 \ucd08\uae30\ud654\ud558\uace0 \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \uae38\uc774\ub97c \ud655\uc778\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h3>3.3 \uc624\ub514\uc624 \ub370\uc774\ud130 \uc2dc\uac01\ud654<\/h3>\n<p>\n        \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \uae30\ubcf8\uc801\uc778 \ud30c\ud615\uc744 \ud655\uc778\ud558\uae30 \uc704\ud574 <code>matplotlib<\/code>\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc2dc\uac01\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<pre><code>import matplotlib.pyplot as plt\n\n# \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \ud30c\ud615 \uc2dc\uac01\ud654\nplt.figure(figsize=(10, 4))\nplt.plot(audio_file)\nplt.title(\"Audio Signal Waveform\")\nplt.xlabel(\"Samples\")\nplt.ylabel(\"Amplitude\")\nplt.grid()\nplt.show()<\/code><\/pre>\n<h4>\uc704 \ucf54\ub4dc \uc124\uba85:<\/h4>\n<ul>\n<li><code>matplotlib<\/code>\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc624\ub514\uc624 \uc2e0\ud638\uc758 \ud30c\ud615\uc744 \uc2dc\uac01\ud654\ud569\ub2c8\ub2e4.<\/li>\n<li>\ud30c\ud615\uc740 \uc0d8\ud50c \uc218\uc5d0 \ub530\ub978 \uc9c4\ud3ed\uc73c\ub85c \ud45c\ud604\ub429\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h2>4. \ud65c\uc6a9 \uc608\uc81c: \uc624\ub514\uc624 \ud30c\uc77c\uc758 \ud14d\uc2a4\ud2b8 \ubcc0\ud658<\/h2>\n<p>\n        \uc774\uc81c \ub85c\ub4dc\ud55c \uc624\ub514\uc624 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc624\ub514\uc624 \uc2e0\ud638\ub97c \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<pre><code># \uc624\ub514\uc624\ub97c \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ninputs = tokenizer(audio_file, return_tensors=\"pt\", padding=\"longest\")\nwith torch.no_grad():\n    logits = model(inputs.input_ids).logits\n\n# \uc608\uce21\ud55c \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\npredicted_ids = torch.argmax(logits, dim=-1)\ntranscription = tokenizer.batch_decode(predicted_ids)[0]\n\nprint(\"Transcription: \", transcription)<\/code><\/pre>\n<h4>\uc704 \ucf54\ub4dc \uc124\uba85:<\/h4>\n<ul>\n<li>\ud1a0\ud06c\ub098\uc774\uc800\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc624\ub514\uc624 \ub370\uc774\ud130\ub97c \ud150\uc11c\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/li>\n<li>\ubaa8\ub378\uc744 \ud1b5\ud574 \ub85c\uc9d3\uc744 \uacc4\uc0b0\ud558\uace0, \uc774\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc608\uce21\ub41c ID\ub97c \uc5bb\uc2b5\ub2c8\ub2e4.<\/li>\n<li>\uc608\uce21\ub41c ID\ub97c \ud14d\uc2a4\ud2b8\ub85c \ub514\ucf54\ub529\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h3>4.1 \uacb0\uacfc \ud655\uc778<\/h3>\n<p>\n        \uc704 \ucf54\ub4dc\uc758 \ucd9c\ub825 \uc624\ubc84\ud5e4\ub4dc\ub97c \ud1b5\ud574 \uc624\ub514\uc624 \ud30c\uc77c\uc758 \ud14d\uc2a4\ud2b8 \ubcc0\ud658 \uacb0\uacfc\ub97c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub807\uac8c \ud568\uc73c\ub85c\uc368, \ub2e4\uc591\ud55c \uc74c\uc131\uc744 \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc5d0 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<h2>5. \uacb0\ub860<\/h2>\n<p>\n        \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38\ub97c \ud65c\uc6a9\ud558\uc5ec Google Colab\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130\ub97c \ud655\uc778\ud558\uace0 \ucc98\ub9ac\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4.<br \/>\n        \uc624\ub514\uc624 \ub370\uc774\ud130\ub294 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ub420 \uc218 \uc788\uc73c\uba70, \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \ud1b5\ud574 \ubcf4\ub2e4 \uc815\uad50\ud55c \ubd84\uc11d\uc774 \uac00\ub2a5\ud574\uc9d1\ub2c8\ub2e4.<br \/>\n        \uc774\ubc88 \uac15\uc88c\ub97c \ud1b5\ud574 \uae30\ubcf8\uc801\uc778 \uc624\ub514\uc624 \ub370\uc774\ud130 \ucc98\ub9ac\uc758 \uae30\ucd08\ub97c \ub2e4\uc9c0\uae38 \ubc14\ub78d\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 \ub354\uc6b1 \ub2e4\uc591\ud55c \uae30\ub2a5\uacfc \uae30\ubc95\uc744 \ubc30\uc6cc \ub098\uac00\uae30\ub97c \uad8c\uc7a5\ud569\ub2c8\ub2e4.\n    <\/p>\n<h2>6. \ucc38\uace0 \uc790\ub8cc<\/h2>\n<ul>\n<li><a href=\"https:\/\/huggingface.co\/transformers\/\">Hugging Face Transformers \uacf5\uc2dd \ubb38\uc11c<\/a><\/li>\n<li><a href=\"https:\/\/colab.research.google.com\/\">Google Colab<\/a><\/li>\n<li><a href=\"https:\/\/pytorch.org\/\">PyTorch \uacf5\uc2dd \ubb38\uc11c<\/a><\/li>\n<\/ul>\n<p><\/body><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ucd5c\uadfc \uc778\uacf5\uc9c0\ub2a5(AI) \ubc0f \uae30\uacc4\ud559\uc2b5(ML) \ubd84\uc57c\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \ud65c\uc6a9\ub3c4\uac00 \uc0c1\uc2b9\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \ud5c8\uae45\ud398\uc774\uc2a4(Hugging Face)\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 \ud2b8\ub80c\uc2a4\ud3ec\uba38(transformer) \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \ud070 \uc778\uae30\ub97c \ub04c\uace0 \uc788\uc73c\uba70, \uc624\ub514\uc624 \ub370\uc774\ud130 \ucc98\ub9ac \ubc0f \ubcc0\ud658\uc5d0\ub3c4 \ud65c\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. 1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \uc18c\uac1c \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub2e4\uc591\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\uba70, \ucee4\uc2a4\ud130\ub9c8\uc774\uc988\uc640 \uac04\ud3b8\ud55c \ud65c\uc6a9\uc774 \ud2b9\uc9d5\uc785\ub2c8\ub2e4. \uc0ac\uc6a9\uc790\ub294 \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ub2e4\uc6b4\ub85c\ub4dc\ud558\uc5ec \uc190\uc27d\uac8c \uac01\uc885 NLP &hellip; <a href=\"https:\/\/atmokpo.com\/w\/29694\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \ucf54\ub7a9\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130 \ud655\uc778&#8221;<\/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-29694","post","type-post","status-publish","format-standard","hentry","category-30"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \ucf54\ub7a9\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130 \ud655\uc778 - \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\/29694\/\" \/>\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, \ucf54\ub7a9\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130 \ud655\uc778 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ucd5c\uadfc \uc778\uacf5\uc9c0\ub2a5(AI) \ubc0f \uae30\uacc4\ud559\uc2b5(ML) \ubd84\uc57c\uc5d0\uc11c \uc624\ub514\uc624 \ub370\uc774\ud130\uc758 \ud65c\uc6a9\ub3c4\uac00 \uc0c1\uc2b9\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. 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