Transformers 17-26.ipynb

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Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"188c48ef-ebe2-4f97-aadb-60cf6276381f"},"source":["# 런타임 3분 소요\n","!pip install transformers sentencepiece\n","from transformers import GPTNeoForCausalLM, GPT2Tokenizer\n","\n","# 모델 및 토크나이저 불러오기\n","model = GPTNeoForCausalLM.from_pretrained(\"EleutherAI/gpt-neo-1.3B\")\n","tokenizer = GPT2Tokenizer.from_pretrained(\"EleutherAI/gpt-neo-1.3B\")"],"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting transformers\n","  Downloading transformers-4.30.2-py3-none-any.whl (7.2 MB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.2/7.2 MB\u001b[0m \u001b[31m97.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hCollecting sentencepiece\n","  Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 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sentencepiece-0.1.99 tokenizers-0.13.3 transformers-4.30.2\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/1.35k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7116aa8568334af0a622c4c7237ac76b"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading pytorch_model.bin:   0%|          | 0.00/5.31G [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"33c44269b9b84d5b9b25b94c20c01c55"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/vocab.json:   0%|          | 0.00/798k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"75e9dbdc6a224d53bbfebb99baf306fe"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d7d9e0c7f94c4ac39598f0063db533e3"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)cial_tokens_map.json:   0%|          | 0.00/90.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"598687be02b34972bbe418c22930c800"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 0.00/200 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"b45b2a039fc6411b9e0e4dc702f5d483"}},"metadata":{}}]},{"cell_type":"markdown","metadata":{"id":"dTmxkzQiDihD"},"source":["#18"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-YFr7Z5xesyK","executionInfo":{"elapsed":5504,"status":"ok","timestamp":1688436215481,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"a61cd44a-5c5c-4525-adda-74d6b362d597"},"source":["# 토크나이징을 통한 인코딩(입력문이 하나인 경우)\n","input = tokenizer.encode(\"I evaluated the performance of GPT-Neo developed by OpenAI.\", return_tensors=\"pt\")\n","\n","# 첫번째 인코딩 결과(결과적으로 하나의 입력문장)를 확인\n","print(input[0])\n","\n","# 첫번째 인코딩 결과를 디코딩\n","print(tokenizer.decode(input[0]))\n"],"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["tensor([   40, 16726,   262,  2854,   286,   402, 11571,    12,  8199,    78,\n","         4166,   416,  4946, 20185,    13])\n","I evaluated the performance of GPT-Neo developed by OpenAI.\n"]}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cLfNYeLLB41-","executionInfo":{"elapsed":454,"status":"ok","timestamp":1688436218941,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"b6a79a10-0b52-42c7-a57e-386a9062e7cb"},"source":["# 토크나이징을 통한 인코딩(입력문이 복수인 경우)\n","tokenizer.add_special_tokens({'pad_token': '[PAD]'})\n","\n","input = tokenizer.batch_encode_plus([\"I evaluated the performance of GPT-Neo developed by OpenAI.\",\"I evaluated the performance of GPT developed by OpenAI.\"], padding=True, truncation=True, return_tensors=\"pt\")\n","\n","# 인코딩 결과 확인\n","print(input['input_ids'])\n","\n","# 디코딩\n","print([tokenizer.decode(input['input_ids'][i]) for i in range(len(input['input_ids']))])\n"],"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["tensor([[   40, 16726,   262,  2854,   286,   402, 11571,    12,  8199,    78,\n","          4166,   416,  4946, 20185,    13],\n","        [   40, 16726,   262,  2854,   286,   402, 11571,  4166,   416,  4946,\n","         20185,    13, 50257, 50257, 50257]])\n","['I evaluated the performance of GPT-Neo developed by OpenAI.', 'I evaluated the performance of GPT developed by OpenAI. [PAD] [PAD] [PAD]']\n"]}]},{"cell_type":"markdown","metadata":{"id":"dE9Vi3MQDgj8"},"source":["# 19"]},{"cell_type":"code","metadata":{"id":"uMW7GPyWCE5T","executionInfo":{"status":"ok","timestamp":1688436227308,"user_tz":-540,"elapsed":970,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"}}},"source":["# 토크나이징\n","input = tokenizer.batch_encode_plus([\"I evaluated the performance of GPT2 developed by OpenAI.\", \"Vaccine for new coronavirus in the UK\",\"3.1415926535\"], max_length=5, truncation=True, padding=True, return_tensors=\"pt\")"],"execution_count":4,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"pzWXx080EDM6","executionInfo":{"elapsed":3,"status":"ok","timestamp":1688436230743,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"1435a44a-b5cf-47c4-8987-be9473a376d6"},"source":["# 인코딩 결과 확인\n","input['input_ids']"],"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["tensor([[   40, 16726,   262,  2854,   286],\n","        [   53,  4134,   500,   329,   649],\n","        [   18,    13,  1415, 19707, 22980]])"]},"metadata":{},"execution_count":5}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"rfgYP8tUE4zF","executionInfo":{"elapsed":12018,"status":"ok","timestamp":1688436246452,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"9dcd6650-e226-4c02-ae2a-4e4eb0823e4e"},"source":["# 인코딩 결과를 model.generate( )에 투입\n","generated = model.generate(input['input_ids'])"],"execution_count":6,"outputs":[{"output_type":"stream","name":"stderr","text":["The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n","Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n","/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1353: UserWarning: Using `max_length`'s default (20) to control the generation length. This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we recommend using `max_new_tokens` to control the maximum length of the generation.\n","  warnings.warn(\n"]}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KIK9Hli6GBp4","executionInfo":{"elapsed":474,"status":"ok","timestamp":1688436250248,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"211fac22-57d2-4e9c-cb86-95fe1899e836"},"source":["# model.generate( ) 결과 건수(len) 확인\n","len(generated)"],"execution_count":7,"outputs":[{"output_type":"execute_result","data":{"text/plain":["3"]},"metadata":{},"execution_count":7}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"VXk4G7ebDnWN","executionInfo":{"elapsed":451,"status":"ok","timestamp":1688436257923,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"fb6da9f6-1528-451f-d7f3-501ea4e2414f"},"source":["# 디코딩\n","generated_text = tokenizer.batch_decode(generated)\n","\n","# enumerate( )는 변수 generated_text에 있는 키값(value)에\n","# 0, 1, 2,...로 시작하는 숫자 키(key)를 부여\n","for i, sentence in enumerate(generated_text):\n","  print(f'No.{i+1}')\n","  print(f\"{sentence}\\n\")\n"],"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["No.1\n","I evaluated the performance of the proposed method on the real-world dataset. The results are shown in\n","\n","No.2\n","Vaccine for new-borns\n","\n","The vaccine for new-borns is a vaccine\n","\n","No.3\n","3.1415926535897932384626433832795028841971693\n","\n"]}]},{"cell_type":"markdown","metadata":{"id":"yP2lNBQTHopr"},"source":["# 20"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":433,"referenced_widgets":["50074639706c4556a44de85e0a661cbb","3e385b4f2e1845f7ae136a171b90fb8f","b4820a6c1be24b919d3a0d70c3b34913","7790c325654e4e429b200dd98cca9bfa","4f2b94e4c2934154ba5d20526a7d074f","cf891c8c537342eeb6f59aab1e6c8131","c821ea0852094622a4ded4526a1e6de1","1afeb54eedb24eed85a9d9a1b15904a7","55c957c3d8c9440fb9eff148a9c40492","93b59eb7958f434fbb3031a2e9fb80aa","d3a95821a9294673aa8a48a6191bb499","85e8514a430148638c443276b8c105e9","3b00b721a4d3463dbab0e863bd83b57b","1f2efddd82ec4ac896b7cabe3e083855","03b5895f4cd44457aa8b38d59ecbb39a","17295b4a2b38419a94bab9476d0f8688","dbdc4ec1bc1a4774b5b7ddc85a04002d","410bd82eda2643a3a29d376bf0524177","34e2217a107244f89f3018ccab36cb19","1c080b78e91f4d75b4a8f1803ae2c7f8","c02ad732f56a492c85ad46f8eba3ab6d","de5e23a350cb4fe7b589b3e997ed04f1","4213e83108044c5b83e009df91e2cdb3","1c56a7194313463da574484c2a0b063c","18c383c75ba54490b92756b0040525ab","58515d941de74418927f5d97a525fff8","f8366d3cc0544bffac357342e5e2a04a","f4377c2aceba4ea6a864bc704e1d9b97","b9b70ed8b05848469e97f28c8e70ea41","7c0f76f4b79d488c846d9cb4412ab57a","2f7093aa2684429cafb6e89b18beb524","2b3e7026c8e74e0aa430e2017a8ba457","6f6b52db97594c59bc5384aed539be64","c84f997716674805b19a50dce9c14f3f","0dd968ebbfbf4cf4b76c7f2d557d5fd5","a59c5a3caaf9470688d063b3300314b6","b1982d95fbcc4df3bbac877e955e0678","237c84ec55bf4916886b03cf06640b5d","f422dd65b703468b9f314e81ee9e30d8","cf911298e0bf4524b823b6c8448af67f","22062092332143b6bed859a3db62f6fe","4bfb673095284329b50d4ac33d6d82e0","2dd87fc7201441639acbb26aece3103b","3f1224e5c24e40d1876cd84eafd02b45","3e288867f3b641cebff5de91d61cb18d","efbdf16476014589a0cf5340baf2b037","82594432b5fe40b096bef9826dc37bc6","d6f428338e2e42e3a4a7ba25d8f00d2e","62e7d3b34f964132aa115539417882da","8ae298b9b97840678aca2e589264280a","613fdeed11dd40c19323fcd1a7c165ff","8e21985808094c13b49a04a2e63df65b","eedfca3b28e748b0b7b9735f82da48e8","f4805a9211674d3387a6f08d02c52338","11aec0b01dc94fbaaec2df3557338453","05b1010866444cc1b24a15a8723fbc8a","63a16f64404a4bceb30b7b7024f99e68","7b38322080f945c2a3b9186b1084d7af","00145117b67d44738cd096fb367d795d","5077707c1b5e42bab441ca980d54e1f4","0d46bae0b9a3474ca39b43bdc5af6be3","48a8e166ece649afa2e71798606c797d","4ed8245a24054c6992759b89799bf0d8","5c1c85e94fbc470fb07f938ad5cd64cb","45ab89a083d84fe19c0dff77dd5de106","16803b0f7911487f8b7ef6a8cddbff37"]},"id":"W-CMslK9F2AE","executionInfo":{"elapsed":10431,"status":"ok","timestamp":1688436277354,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"b1842f90-7f7f-48ef-f1db-99a820d85ea2"},"source":["# 코랩 메모리가 clear된 경우만 transformers 재설치\n","# !pip install transformers\n","\n","# 모델 및 토크나이저 불러오기\n","from transformers import AutoTokenizer, AutoModelWithLMHead\n","\n","tokenizer = AutoTokenizer.from_pretrained(\"distilgpt2\")\n","\n","model = AutoModelWithLMHead.from_pretrained(\"distilgpt2\")\n"],"execution_count":9,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/762 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"50074639706c4556a44de85e0a661cbb"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/vocab.json:   0%|          | 0.00/1.04M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"85e8514a430148638c443276b8c105e9"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"4213e83108044c5b83e009df91e2cdb3"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.36M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"c84f997716674805b19a50dce9c14f3f"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/transformers/models/auto/modeling_auto.py:1362: FutureWarning: The class `AutoModelWithLMHead` is deprecated and will be removed in a future version. Please use `AutoModelForCausalLM` for causal language models, `AutoModelForMaskedLM` for masked language models and `AutoModelForSeq2SeqLM` for encoder-decoder models.\n","  warnings.warn(\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading model.safetensors:   0%|          | 0.00/353M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"3e288867f3b641cebff5de91d61cb18d"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)neration_config.json:   0%|          | 0.00/124 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"05b1010866444cc1b24a15a8723fbc8a"}},"metadata":{}}]},{"cell_type":"markdown","metadata":{"id":"u-n9rtMGIFnq"},"source":["# 21"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mi1CADfzHqVb","executionInfo":{"elapsed":458,"status":"ok","timestamp":1688436287675,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"bc895d9f-ce4c-456c-cc95-fcd372584232"},"source":["# 토크나이징. 출력은 파이토치 텐서(pt)로 받음\n","input_ids = tokenizer.encode(\"I like gpt because it's\", return_tensors='pt')\n","\n","# max-length 값을 12로 설정\n","greedy_output = model.generate(input_ids, max_length=12)\n","\n","# *표시를 100번 실행하여 *로 구성된 줄 만들기\n","print(\"Output:\\n\" + 100 * '-')\n","\n","# 인코딩 결과 디코딩\n","print(tokenizer.decode(greedy_output[0], skip_special_tokens=True))\n"],"execution_count":10,"outputs":[{"output_type":"stream","name":"stderr","text":["The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n","Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"]},{"output_type":"stream","name":"stdout","text":["Output:\n","----------------------------------------------------------------------------------------------------\n","I like gpt because it's a good thing to have\n"]}]},{"cell_type":"markdown","source":["## 22"],"metadata":{"id":"eoTMp-OztkhO"}},{"cell_type":"code","source":["# 모델 및 토크나어지 불러오기\n","from transformers import AutoTokenizer, AutoModelWithLMHead\n","\n","tokenizer = AutoTokenizer.from_pretrained(\"microsoft/DialoGPT-small\")\n","\n","model = AutoModelWithLMHead.from_pretrained(\"microsoft/DialoGPT-small\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":377,"referenced_widgets":["f9fc6e4ae74d4b2e980583eefe7a6622","0d78fe15128d4095898cc989aadbce1a","c919dd5347dc4f269033135b4e55bb2e","6f75eb72520840e9801520d8194383c0","3d3eeb2a7aae45f3b4e7254f9891046b","6f79648bcf0045f6934a64df4e9c92ab","615cff3eb0674572ba127892a0362dd9","d1ccef509dff43978e3b31d49d00a8f8","26cff237a73448689ade95f69dcb6aa2","d1fa33c3cf8646718ccfdb8b061b727d","a7f15dcc6d2d45a482a9f0535c1cfbe4","3a7ec4566b85459892a15baa715047a7","7da565fac0d34094b7a0e2bdea59ca83","13222274e60347e89ae0eb6928eacd4a","1c3824b62213451ba683d9eb94e04942","bd3a82f2e85945b299fd413f41e4c967","6131787af39d4f8bb2e67fafaed09110","f9042e04274d437c91b969dd2d0cce69","77a72b73607b49db957d00f316f1bacc","ac1dbdb3c3754947a426406bd59c12ec","0a8594cac6d24e86b8db9b4fb7a7a7b7","804850485e60425793e0ad4143af534f","00bff3ad052446f9b2310c2d6764b275","72c75765cca54878adca436c6c7f3461","ee7516581ed14a94a11fac574095f103","44a452ac46ee43029b312a7efa9ffdba","57bd3f04a6704fda83a1cd432538592d","779b140fbf0e41f2b9cee1dbba708fc9","a7293c3ca6954d1bbba68e4a541f4966","96e87e5cdd3746399cf390cddd29cab2","349291b835a646ef8856b38b6f46ff83","a6ac4da532fb460d87e0f4183a59cdba","56f81c92280c4703983ab17a5181bb8b","06fb1d07ee6641c89ad62e6f35c7770b","d69f3dfd15d84f3e96c425df2ec00dda","192697c589444bdcbf4a7676d0a9a759","03f8bc20a4484b0eb7032eac55fda2eb","6e1c9c643795450d8f57f1c69f6240a5","9aebabf7c5744156ad589e97ee0dccfe","a90c184904564be39e7d67b5c08a8059","5750cc5d44c04944879e2ca3f7ab9fb8","ee1dc3cc91054a7690fe2648420622d8","9c936f8202bf4a04b3b7f53c3302ccf4","6c4fbdfd673e4a7eb15295938d445438","6dd599a23b734cca8cb0228b77957dfb","9a20084f43a44f26a200870c1e4a4ebb","889e3cb5359644bcbf3a49de4e3bb1a8","6e8352a3d6f945cb849969f96cb1af3d","05fbebb26c2847f89fcee50add7211b6","171d16195b9d4fbdb2beda906f73f72f","b4bec5e75b674ff2bc374c5e80d2dfcc","3b52e8cb2b084a20ace065fd565aed3a","6a009e4c39a642b4b83fcb0bed2eef33","952d9f0bee834eec921b1bb3afb0150f","d2ee1781bee14ffaacb1c12358469fed","1960125bf978466398f4f9ef8e772fea","477d2b1fad1e4ea49333495fff075a50","30c6907e2ada43f48d9fb9b0109faed5","39821ad3699143d8a6f9a2cfaa6fb76f","b62311a39c344219bb6f9d06c75fd9c1","e23b931634f64bea928f41ab9ba2de1e","149864790ce84d47ab60917961e3afa7","7ef343236b4d459292310964ad7b75e7","df808878600c4e15a0a4e219a77b5e59","677b5fe7eec34d85a22a23f9403904ed","634a27ce0e044b0b81aaad461400ca71"]},"id":"mfus-Fc2tpjA","executionInfo":{"status":"ok","timestamp":1688437530561,"user_tz":-540,"elapsed":7545,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"}},"outputId":"9a97fea1-8831-49f5-de81-f15f3d7bacbf"},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 0.00/26.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f9fc6e4ae74d4b2e980583eefe7a6622"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/641 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"3a7ec4566b85459892a15baa715047a7"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/vocab.json:   0%|          | 0.00/1.04M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"00bff3ad052446f9b2310c2d6764b275"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"06fb1d07ee6641c89ad62e6f35c7770b"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading model.safetensors:   0%|          | 0.00/351M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6dd599a23b734cca8cb0228b77957dfb"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)neration_config.json:   0%|          | 0.00/124 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"1960125bf978466398f4f9ef8e772fea"}},"metadata":{}}]},{"cell_type":"markdown","source":["# 23"],"metadata":{"id":"s1PgqpPjuHQe"}},{"cell_type":"code","source":["# 토크나이징\n","input_ids = tokenizer.encode(\"I like gpt because it's\", return_tensors='pt')\n","\n","# max-length 값을 30으로 설정\n","greedy_output = model.generate(input_ids, max_length=30)\n","\n","print(\"Output:\\n\" + 100 * '-')\n","print(tokenizer.decode(greedy_output[0], skip_special_tokens=True))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"UXwIf3VluSJD","executionInfo":{"status":"ok","timestamp":1688437666200,"user_tz":-540,"elapsed":936,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"}},"outputId":"5ac3523b-65e8-4e20-cf87-12738f2f66d8"},"execution_count":13,"outputs":[{"output_type":"stream","name":"stderr","text":["The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n","Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"]},{"output_type":"stream","name":"stdout","text":["Output:\n","----------------------------------------------------------------------------------------------------\n","I like gpt because it's a good way to get a feel for the game.\n"]}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"tGYo1THIIUke","executionInfo":{"elapsed":460,"status":"ok","timestamp":1688437676487,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"f339ef35-2fb7-4613-88e7-0209fa82914b"},"source":["# 보너스 코딩: 다른 예문으로 추가 코딩\n","# 토크나이징\n","input_ids = tokenizer.encode(\"Covid19 delta is spreading\", return_tensors='pt')\n","\n","# max-length 값을 50으로 설정\n","greedy_output = model.generate(input_ids, max_length=50)\n","\n","print(\"Output:\\n\" + 100 * '-')\n","print(tokenizer.decode(greedy_output[0], skip_special_tokens=True))\n"],"execution_count":14,"outputs":[{"output_type":"stream","name":"stderr","text":["The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n","Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"]},{"output_type":"stream","name":"stdout","text":["Output:\n","----------------------------------------------------------------------------------------------------\n","Covid19 delta is spreading the word\n"]}]},{"cell_type":"markdown","source":["## 24"],"metadata":{"id":"VzYLeXtVxVca"}},{"cell_type":"code","metadata":{"id":"OtNVbaLtbvTH"},"source":["# 코랩 메모리가 clear된 경우만 transformers 재설치\n","!pip install transformers"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":752,"referenced_widgets":["c2d670c56f4e43dca0b1fbb4a25963a5","140355ab05e944adb082a531fc221c2a","3d0ee8c59bbe45f1b2d7f261fa0b3378","8c4de0c767a248fcb4f9c1c403e6b32c","7f5aa68964e14554a6f46b23c8a31add","7aa30f18dd0345818197be0af15a782a","04a8388eb3264937ab859f1609214499","701557c0046c4da7aa4c42c6b06b319c","820e8b54bc9d4c8c926ca02a9e9ec5cc","a9abf56f47a3496c932065e2a428d8b7","5ec5ab93a94349ac9f7ce152f7282ad3","25ab931cb052470fac0450ba26ec766e","340dcb1598544223a236bf769333a60f","195d3229b4c44ad7802d67eec2ef005c","ade920ae7a1b4cc686c7b11b3957c8ef","f86fb273276f475bbf12e87f7dc12a8c","d0e96741457a490ea609e16c00c83d9f","df57071c9a614617bdeafb29fe6edd86","00b613133acd46d8a44c590848136083","f8e31329dff344489f2d97a5ff258863","e642d408e9bd4cb4a5c77f4e249fffda","95b1529fb4f74aaab627a0411b306305","47ae9fd6b082469d91159ae45a7507a2","f9ebaf1351404afa94538580e8c04b0c","ae36096e320642cfb7aa787d6025d6c7","b7cf76c438c54defa42f576807572c4b","bdfba0beb4d7435daae325e935bceb30","330448aefb2f4988a7b53e0117ad915f","60e51403506a4abc906242c603e5a127","ab6ce94533d24472a2600648663d2a80","f85a3db7473d45efa381ab31b23244df","3d747714f47c44279fd55975996eb957","dcb00892f8174891ad2006bc4afa9a53","7415f7dec38f43f3b4dc22984c2f83ba","42888ed6711c410382a3444839a5f3ad","412dac7fde4a437083bb8720cf941a54","0be4c507c536448da7e4286d9989f04c","ee33135e027946da92c79fbee19d144d","4d7a26eaa119451a92ed0d86a57eb10d","ede4fa4a21324d48a925b66ef5e76820","ebfd89bb00ff431ebf2f6e3d9c597392","abd346854b0e441183c6ff7b7a68fd5d","3c8e38cf30244e629594e7ea863ad695","1d1233dcf1f54966b28f73abcaa4f7fa","7a5c706b17c84466a5ae191d560b628c","63447529de074727ad341bc152cd0097","5e4f908e14244f58ad3a357c43de1420","42e22ac502a94db9906aac01639c6d17","f8791f4372754c0bbb72c79d6433e92a","40847f9065984179803ec4fe91ba55e9","8512c9347dbd4926aeb8f2bf65d4d4dd","41988ef276c34c6a86dcfa015be58930","4e6a7ed884fd43eba33406f3edc2e71c","ae3fd8fcb01f4d78bb23bd241550faf8","6001b60417c74a3797cefb791572608f"]},"id":"KTEjg25XUgWl","executionInfo":{"elapsed":9842,"status":"ok","timestamp":1688438433912,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"4b299f75-6dab-47aa-d75e-8271c50c7700"},"source":["# transformers 라이브러리에서 pipeline 불로오기\n","from transformers import pipeline\n","\n","# pipeline에 과업(fill-mask) 및 모델 지정\n","unmasker = pipeline('fill-mask', model='bert-base-uncased')\n","\n","# pipeline을 인스턴스화한 변수 unmasker에 [MASK] 토큰을 지닌 입력문장 투입\n","unmasker(\"MLM and NSP is the [MASK] task of BERT.\")\n"],"execution_count":15,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/570 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"c2d670c56f4e43dca0b1fbb4a25963a5"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading model.safetensors:   0%|          | 0.00/440M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"25ab931cb052470fac0450ba26ec766e"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForMaskedLM: ['cls.seq_relationship.bias', 'cls.seq_relationship.weight']\n","- This IS expected if you are initializing BertForMaskedLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n","- This IS NOT expected if you are initializing BertForMaskedLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 0.00/28.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"47ae9fd6b082469d91159ae45a7507a2"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)solve/main/vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7415f7dec38f43f3b4dc22984c2f83ba"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)/main/tokenizer.json:   0%|          | 0.00/466k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7a5c706b17c84466a5ae191d560b628c"}},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["[{'score': 0.257278710603714,\n","  'token': 2364,\n","  'token_str': 'main',\n","  'sequence': 'mlm and nsp is the main task of bert.'},\n"," {'score': 0.20740698277950287,\n","  'token': 3078,\n","  'token_str': 'primary',\n","  'sequence': 'mlm and nsp is the primary task of bert.'},\n"," {'score': 0.06773308664560318,\n","  'token': 2034,\n","  'token_str': 'first',\n","  'sequence': 'mlm and nsp is the first task of bert.'},\n"," {'score': 0.06548508256673813,\n","  'token': 2430,\n","  'token_str': 'central',\n","  'sequence': 'mlm and nsp is the central task of bert.'},\n"," {'score': 0.061674028635025024,\n","  'token': 3937,\n","  'token_str': 'basic',\n","  'sequence': 'mlm and nsp is the basic task of bert.'}]"]},"metadata":{},"execution_count":15}]},{"cell_type":"markdown","metadata":{"id":"kUzmXu5kbX3k"},"source":["# 25"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":678,"referenced_widgets":["81c1adadf5054926abb0e7edc0d8e495","fdcfae11993a426fbb06d6aad241df3c","2a7b9f4456f04f2187a3e1bcd2eace9b","fd726e1f312a4645a2bc80cbde5a0f2f","a7be0c49059441bba50d7f2141671c35","6782cc6ff7854a6bbfd48d3aee7e0639","53f6e19936fc4a15900a487168c5afff","1d5d10b588af42ba923f32d00492b0b4","3d5848c0d99e467e8514a9099fc4d41c","16a27c100f344deeaec2c0f6a4e8c9b8","b5e6b3d75e2241eb8c1317c3eb528a8e","21d4aecad2504b2b854755040f31d0a4","ec1fe1ccddf04b99add11ceb9b421797","2323a1b10f5d4eeba0faeba982486992","fcc6cc7a74814d16a532f7c1eb3bb281","db1f6872a5564b75bb6f3f7a6fd4119d","e5c72086298044cf88f4297e61f82305","955e4f0196f847c8bec534c7c6b1014b","89c3e7470f7244ed843f176eb027e5db","149c8da0fbce43cab419909f27fbb061","d27071598efd4090b9a1ae0521f2a1f3","fd66ba9429a747129847734ea201ef04","5188962ff47f46ba9f11c7a9c7cf6add","633b39fb0cf94a0cb36cfba286d4130a","32f6b43e186e4f19b2f5e094ed7a4e40","2695e9ecb5da42818435a18c4bccfaae","e45d5ff4b55646caa7c197013de24016","65ea31f948564d55894038122a76af9e","f6d5a5020332411dbbc592c744a6ac10","8613958a41d242cd8fe235fc6673c746","e89bb5ff3844443fba63a9b7ca849d43","867ae218c96b41c2836e4ee1f645264d","f4855dd10474488798da968a4b8038ea","8aeb39f6284f4d7ab2b632ae48f95155","1f7d5ca15f434de0a1ccddc8287cd953","950c3f9d37924c76b7bc174d176741c6","edaac8da1a514948937f0221610f1416","475f8ffe52aa499aa8c49f6d0620a541","63cb0dc550ff453c90d65cb85cf96225","ddab4bb3f7cc42a8bfa9798b0da3ed02","af422412c8f94ef3995016004d15cf3c","a9d7ad0cff68426db2212f15112c68d3","0614efee37854c37993fa0caa09d5761","bf923e06a78341fd82b64882b1199c7d","7185a079d097414ea7dff33c561aea99","37fcef4654fc403bb1d054bd4c2172e1","2ed0f8a78f484a04a0c6d7f73a405749","8f58dc55b6fa47148cd674f1c30cf827","5b021ff5a7364b0d8ccfaada34d70486","0ae510c0ab624178bde875735705c7e7","c40bac2e247244deaed362abb205c3fe","afb376fc36764b4197b4d6a5a2c9f236","2686e2c6fc664e3aa2424e971fc6792a","b2af0b5c2b5b472fa88f86392e306939","da99d1a479fa4a809cb74193dbeaec83"]},"id":"Kq7LqBATzKlu","executionInfo":{"elapsed":6433,"status":"ok","timestamp":1688438455429,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"ea86e581-ddba-4a74-d179-4bd8e6cfaa94"},"source":["from transformers import pipeline\n","\n","# 모델명이 바뀌었음에 유의\n","unmasker = pipeline('fill-mask', model='distilbert-base-uncased')\n","unmasker(\"MLM and NSP is the [MASK] task of BERT.\")\n"],"execution_count":16,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/483 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"81c1adadf5054926abb0e7edc0d8e495"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading model.safetensors:   0%|          | 0.00/268M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"21d4aecad2504b2b854755040f31d0a4"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 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'main',\n","  'sequence': 'mlm and nsp is the main task of bert.'},\n"," {'score': 0.08182773739099503,\n","  'token': 4563,\n","  'token_str': 'core',\n","  'sequence': 'mlm and nsp is the core task of bert.'},\n"," {'score': 0.040237803012132645,\n","  'token': 7037,\n","  'token_str': 'dual',\n","  'sequence': 'mlm and nsp is the dual task of bert.'},\n"," {'score': 0.024844937026500702,\n","  'token': 4054,\n","  'token_str': 'principal',\n","  'sequence': 'mlm and nsp is the principal task of bert.'}]"]},"metadata":{},"execution_count":16}]},{"cell_type":"markdown","metadata":{"id":"Y_Zb__OPc6ew"},"source":["# 26"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":618,"referenced_widgets":["4374d00aa1ed499e95dd1d89a3f1b899","416133581a0d4f86bc0b5bf30a0c928f","b0766606f7b64bce9e851937bd3e5e23","79b6ae237c944a9887ffbae4a4e403a5","6461bc6484d1474294eb34607678e669","ac35b6f440b041ee9961a7de1222a58e","765d8d3813e64e8c9aa750910d30456d","708170842c1740109dc0abef2d09c23f","94bcad1280df4e6daecaef542bada223","172072f23a5f4003a715bc07fcc7cd14","00db136d7c6d4bb789c26a4ad9d923b0","59c929f0b85a45f3b4c378284e9267c9","7a41d1f2d86c4b859c7ee8ada61b64ce","d6a9b53abe0a4fa784d3cc7b8dda4e85","c62619c4b7ff45a583605e6bb5d567ea","1a003573df9842ba958b0c2bb2e7bbb0","528ac36c02de487f83268917e0db8103","86e28309edcd424bb1cb865b6ec3ccc1","9445fbce0f824977b773a406e25e0dc4","438fe0918f7c40b0ac157f9a08fb256c","e11cd2e186ed4d2b88e6657e94fe7d1e","82e6416e5db3401a8777062d53a07935","d9c0c8759c4547a4ab59968dec2e9a97","6c05d86293b14f09a6d0695792cfa238","816147b5db8d4c62b1644f0332f24e9e","a3d798197bf34241ad0c752f04d98575","593c5bd58e284a5ea5c4013d4ef5b83f","7446cd5392364341839e7dc66e70ca09","a29c2cd777d141d1b42140211c90c748","e6ff9a8d37634a6bbf67b13f0a7c1a78","175dfddb46ce498c96b873036f4b8a68","fcdbb725bb764ad28a4a2181a5a2979d","1100d5a0251f48ea9fb2b69a854cf890","e9c1b545e456471ca6bb275e75887591","4ff9da5b885f4a81b876cdeab42f4ee1","5a903525b5fa4e808cfb112e3a640c49","f87dcbb01fdc432ba57554e55bcd12d0","824150bf540143d280a7e6b59318a836","facd9e6ed87249fc9d6326d544d95b27","e03801d37e664d3ca6d14f7afe320d52","a3071dd8242d4c2e9a0d25b8c9fa75b2","5289ff7de3394a46a2ddb613963e0a3e","bbc427a6e46144969cba43c831d13d9b","7fc3b5c1630542c492c6c2a095b931d4"]},"id":"011u_S5DbtBE","executionInfo":{"elapsed":4902,"status":"ok","timestamp":1688438467208,"user":{"displayName":"Jason Book Yim","userId":"02824935638305274154"},"user_tz":-540},"outputId":"02f062d6-dd5b-4e4c-cfb6-8aea4a430a6c"},"source":["from transformers import pipeline\n","\n","# 모델명이 바뀌었음에 유의\n","unmasker = pipeline('fill-mask', model='albert-base-v2')\n","unmasker(\"mlm and nsp is the [MASK] task of bert.\")\n"],"execution_count":17,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/684 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"4374d00aa1ed499e95dd1d89a3f1b899"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading model.safetensors:   0%|          | 0.00/47.4M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"59c929f0b85a45f3b4c378284e9267c9"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)ve/main/spiece.model:   0%|          | 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'token': 407,\n","  'token_str': 'main',\n","  'sequence': 'mlm and nsp is the main task of bert.'},\n"," {'score': 0.018088163807988167,\n","  'token': 18369,\n","  'token_str': 'foremost',\n","  'sequence': 'mlm and nsp is the foremost task of bert.'}]"]},"metadata":{},"execution_count":17}]}]}