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"overflow_x": null, "grid_auto_flow": null, "grid_area": null, "grid_template_columns": null, "flex": null, "_model_name": "LayoutModel", "justify_items": null, "grid_row": null, "max_height": null, "align_content": null, "visibility": null, "align_self": null, "height": null, "min_height": null, "padding": null, "grid_auto_rows": null, "grid_gap": null, "max_width": null, "order": null, "_view_module_version": "1.2.0", "grid_template_areas": null, "object_position": null, "object_fit": null, "grid_auto_columns": null, "margin": null, "display": null, "left": null } } } } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "KuvW3fmor6Tu", "outputId": "d036dc39-11e5-460c-edf5-1eda20aa109b" }, "source": [ "!pip install transformers\n", "!pip install pronouncing\n", "!pip install wikipedia\n", "import torch\n", "import pronouncing\n", "import wikipedia\n", "import re\n", "import random" ], "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting transformers\n", " Downloading transformers-4.12.3-py3-none-any.whl (3.1 MB)\n", "\u001b[K |████████████████████████████████| 3.1 MB 12.0 MB/s \n", "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers) (2.23.0)\n", "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from transformers) (21.2)\n", "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers) (4.62.3)\n", "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from transformers) (4.8.2)\n", "Collecting pyyaml>=5.1\n", " Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)\n", "\u001b[K |████████████████████████████████| 596 kB 55.7 MB/s \n", "\u001b[?25hCollecting huggingface-hub<1.0,>=0.1.0\n", " Downloading huggingface_hub-0.1.2-py3-none-any.whl (59 kB)\n", "\u001b[K |████████████████████████████████| 59 kB 5.8 MB/s \n", "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers) (3.3.2)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (1.19.5)\n", "Collecting sacremoses\n", " Downloading sacremoses-0.0.46-py3-none-any.whl (895 kB)\n", "\u001b[K |████████████████████████████████| 895 kB 55.1 MB/s \n", "\u001b[?25hCollecting tokenizers<0.11,>=0.10.1\n", " Downloading tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB)\n", "\u001b[K |████████████████████████████████| 3.3 MB 43.7 MB/s \n", "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in 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/usr/local/lib/python3.7/dist-packages (from requests->transformers) (1.24.3)\n", "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (7.1.2)\n", "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.1.0)\n", "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.15.0)\n", "Installing collected packages: pyyaml, tokenizers, sacremoses, huggingface-hub, transformers\n", " Attempting uninstall: pyyaml\n", " Found existing installation: PyYAML 3.13\n", " Uninstalling PyYAML-3.13:\n", " Successfully uninstalled PyYAML-3.13\n", "Successfully installed huggingface-hub-0.1.2 pyyaml-6.0 sacremoses-0.0.46 tokenizers-0.10.3 transformers-4.12.3\n", "Collecting pronouncing\n", " Downloading pronouncing-0.2.0.tar.gz (17 kB)\n", "Collecting cmudict>=0.4.0\n", " Downloading cmudict-1.0.2-py2.py3-none-any.whl (939 kB)\n", "\u001b[K |████████████████████████████████| 939 kB 12.7 MB/s \n", "\u001b[?25hBuilding wheels for collected packages: pronouncing\n", " Building wheel for pronouncing (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for pronouncing: filename=pronouncing-0.2.0-py2.py3-none-any.whl size=6252 sha256=8bfe9404af06ab71c099a0e0de30dd74c44034a93c9b58358e698079eef45525\n", " Stored in directory: /root/.cache/pip/wheels/09/e8/c0/3606d42fdbf5f3871564eb6a353591a8f5deeed013fdb73921\n", "Successfully built pronouncing\n", "Installing collected packages: cmudict, pronouncing\n", "Successfully installed cmudict-1.0.2 pronouncing-0.2.0\n", "Collecting wikipedia\n", " Downloading wikipedia-1.4.0.tar.gz (27 kB)\n", "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.7/dist-packages (from wikipedia) (4.6.3)\n", "Requirement already satisfied: requests<3.0.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from wikipedia) (2.23.0)\n", "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.0.0->wikipedia) (3.0.4)\n", "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.0.0->wikipedia) (2.10)\n", "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.0.0->wikipedia) (1.24.3)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.0.0->wikipedia) (2021.10.8)\n", "Building wheels for collected packages: wikipedia\n", " Building wheel for wikipedia (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for wikipedia: filename=wikipedia-1.4.0-py3-none-any.whl size=11696 sha256=b9f747f6afd4302122ec39dbf95c5b5e77ea31204acf70e40f9871e7f556ea84\n", " Stored in directory: /root/.cache/pip/wheels/15/93/6d/5b2c68b8a64c7a7a04947b4ed6d89fb557dcc6bc27d1d7f3ba\n", "Successfully built wikipedia\n", "Installing collected packages: wikipedia\n", "Successfully installed wikipedia-1.4.0\n" ] } ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 333, "referenced_widgets": [ "032181bf836242fcbec0ab4a0514b29b", "f7bee1ff59124c64b38c4604af077851", "e8f972ebe99e458bbf2a0953fda9ab82", "170ac77f374e42feb9e1bff6e80a7dbc", "124d8bbfb73d44a4940be38920d91572", "5f9865a9cf2d4023b583648904bfb134", "ad7c740633c440d48f9300d8c06830a1", "8dcc5987e043421a981f21b6df250b8d", "999e391cf61b489b8b2ed8343b5d9e8c", "6f61901044cc40459f33277dbb39d049", "a3db55cd6978455787d5233016290d91", "3c9086edb89b4efbb95699b4d892f917", "c959da2639d544be82ab31885ccb006a", "ac2f6c40d37449b68c015eb4a97bfdb2", "7fcc7f8eeaaa4658a54d9e66e6875d77", "0e4036be02b4422faa8615ecdcc59ad3", "3e768a2af2fb41eb9b5c9038f393f86f", "8cf01e31e6c34aac889f4f198afee7eb", "29e358fe2dee40498a0487b18082ddfa", "8099109553a345588c51610d325e35d1", "b81c5722f85f4f24a81180cc4fdb6e8e", "958e796e7bc347e2a99441339f92476e", "6658105526f14e4a951bc1146ef089ed", "d877c381f6d74a99b93d625bfdb0ee56", "533a5a8f620f4b33a5d2aadb2ba40885", "8179f7d645004633a61a245ee1670dee", "94e663762f104da188072a2886b1337e", "8eac561cf2824022a3df82ac4327e46a", "33d7bcd6c510453f86604251ddd86d9b", "ebe524680f0d4e49a41b293bcaa322e5", "36d32d74482e40319a7cc1ed557e54e3", "a5a1f5be7ece43b7b6367819aef2f1e3", "d0a298c84a254d239ef498e533156eee", "1ee3754e5aa247c6b7dc24be8c21ad07", "245d89c8a42146038e97c98294236750", "1a0c3760dec0491eb978a3f0df85d479", "46681d6ebdfc47f782b3b76697af9f99", "00575819891e406794b46153cee8784f", "4ff791c058e7419495f4dd3d9e698b6e", "89f8befa862c4c929c67c02fe7b73ed7", "75cc67137f7a4942902574dc661da179", "b6a13b3c087948e1826ef56826d15b2d", "245d50c66b7a4c04b5921d3ae3a1fd20", "e18176e2147a4ea4bf629a0549f81c25", "426bd6339e884721b19bc791897fe21d", "a5668718f39c4954b05175bb315eda92", "f6fb7a30096948c2a52d7eeb08ad6b60", "694139c7d8c8495787f7f1578d2179fb", "dc01413c22484fc896feca266847b2ec", "f984d16f87dc4691abd608792f494345", "5cad9c3284c240a99b9c6df84577349b", "488c8cdb2b264eada6578b486987a882", "5bbbcb10c4d44b05b6f1626a8817fafd", "42ecfbaf248c403abbe1341abae6fe2e", "bf6f14c13c6f47cf849256f230f56f4b" ] }, "id": "AIRsE899r-53", "outputId": "4e1214e2-9261-4da6-d170-94143d9df469" }, "source": [ "from transformers import RobertaTokenizer, RobertaForMaskedLM\n", "tokenizer = RobertaTokenizer.from_pretrained('roberta-base')\n", "model = RobertaForMaskedLM.from_pretrained('roberta-base')\n", "\n", "def set_seed(seed: int):\n", " \"\"\"\n", " Helper function for reproducible behavior to set the seed in ``random``, ``numpy``, ``torch`` and/or ``tf`` (if\n", " installed).\n", "\n", " Args:\n", " seed (:obj:`int`): The seed to set.\n", " \"\"\"\n", " #random.seed(seed)\n", " #np.random.seed(seed)\n", " #if is_torch_available():\n", " torch.manual_seed(seed)\n", " torch.cuda.manual_seed_all(seed)\n", " # ^^ safe to call this function even if cuda is not available\n", " #if is_tf_available():\n", " #tf.random.set_seed(seed)\n", " \n", "def get_prediction(sent):\n", " \n", " token_ids = tokenizer.encode(sent, return_tensors='pt')\n", " masked_position = (token_ids.squeeze() == tokenizer.mask_token_id).nonzero()\n", " masked_pos = [mask.item() for mask in masked_position ]\n", "\n", " with torch.no_grad():\n", " output = model(token_ids)\n", "\n", " last_hidden_state = output[0].squeeze()\n", "\n", " list_of_list =[]\n", " for index,mask_index in enumerate(masked_pos):\n", " mask_hidden_state = last_hidden_state[mask_index]\n", " idx = torch.topk(mask_hidden_state, k=5, dim=0)[1]\n", " words = [tokenizer.decode(i.item()).strip() for i in idx]\n", " list_of_list.append(words)\n", " print(\"Mask \",index+1,\"Guesses : \",words)\n", " \n", " best_guess = \"\"\n", " for j in list_of_list:\n", " best_guess = best_guess+\" \"+j[0]\n", " \n", " return best_guess\n", "\n", "sentence = \"Manchester United are ___ ___ ___ champions.\"\n", "print (\"Original Sentence: \",sentence)\n", "sentence = sentence.replace(\"___\",\"\")\n", "print (\"Original Sentence replaced with mask: \",sentence)\n", "print (\"\\n\")\n", "\n", "predicted_blanks = get_prediction(sentence)\n", "print (\"\\nBest guess for fill in the blank :::\",predicted_blanks)" ], "execution_count": 2, "outputs": [ { "output_type": "display_data", "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "032181bf836242fcbec0ab4a0514b29b", "version_minor": 0, "version_major": 2 }, "text/plain": [ "Downloading: 0%| | 0.00/878k [00:00 champions.\n", "\n", "\n", "Mask 1 Guesses : ['the', 'defending', 'currently', 'reigning', 'crowned']\n", "Mask 2 Guesses : ['reigning', 'defending', 'the', 'crowned', 'Premier']\n", "Mask 3 Guesses : ['League', 'league', 'defending', 'world', 'four']\n", "\n", "Best guess for fill in the blank ::: the reigning League\n" ] } ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 195, "referenced_widgets": [ "7cacdaa166a54684950b1c375f4bb4ae", "51df5e0baf504a36a21e92b8f4d779dd", "d06143b7125d499bbece7884a686f925", "f0d6b4f323e8469bba41f43a73ade471", "7cb0df68f7df48aea724a83c88b1c0dc", "e0a4c7b059c84fa5abfa55b193e1742f", "73b98453d3e34b0284ca1cec839a4d28", "a5036d5aa4284366af542de292448489", "ed2f3944fa6e4d5983d54d26d5a71d5f", "de23386df2eb47fe9ea712c444615625", "97252e56052d49dba3dd86998e21583f", "9f6e0719b44a436ca715e7c4a9ac9a15", "4da3d8eb23864febb97498e72a77187a", "677a348c48ed441195127a025fc23f02", "d14a30b3f7bc4fb5b9ea89371b7694d4", "9b09794e5cf043f4876648a238db1114", "a93c02b91b314d42a807e13a2ea1f326", "e7c547a057ee49b3a79403ab790a603a", "84a0bd769980438689d1d610dd7e8820", "47809f4fd8e94571b54bda8c07c017dd", "9107e7e766bc4b8499138329edfcb0ab", "7cd6dc4db7574015a6d4616b9d8b496d", "48623a103cf34c9fa083b341dbf0434a", "6a617c9fcdbd490f89efd6ab0956943b", "08bbf0095e7b45b1b8169ead588ef3b8", "7e7131e85bcc4090ab5b5fd56a192553", "465786fbf02849b89996e6d7349f0d5b", "d35884c51a6149198df000ded2626259", "7520e899949f4db5a3d0169c6c872f45", "dba6221aad7644e68e2355e47c963520", "016e8715eeff48aebdea944ed417981b", "6fff05b76c914f60b548448e609881e8", "24d0c02693784108a0548d177c2255ce", "572517ad9a0a46189c06726ca50fb40f", "b1aa5b2aa38247a19570b6adc08c5ec1", "cca18f12e8654ad3b52f71da44dee780", "040f68e426084b70ae6b35e5cb3ed288", "c531f2ef06d04386a6ae0350eb3c17c9", "31a622ad9fc14d50a783311d37034fe9", "a33680cf286e45c387f09fdd07737f5c", "74eba9fad0a0461884f32f2dcba7fdd4", "c67eb55f1a7f4cb6946aa0b7b9c772ec", "338a5fb4b3bf44118493df5c687b2dca", "7ee506753e8244a883133bf24b63de3c", "bf828ad1e5f1454d8fb3dde3eb1fc839", "6811c5cf24ea492cba4a165eb6333dad", "a9cb2ab3d93e4b7c886b2f535522c60b", "fb6116ed268e47289766a617fb4b0101", "fc0bf84a0d6e48e385ba1eb9ba1cea43", "d4f36ebdde44449599aaae3980737580", "a42ea3a1a352413aab7f8770fc0acabd", "e360f95a5ece4d479c79155e9f6ff68f", "a881b52c500d4982b77ebb5be0c4a0c6", "f3b25ed332474490a30d5905bcd85d0d", "67533170fc8d429387fdf570a0e99449" ] }, "id": "kxCLYhe7Jsdn", "outputId": "97b13ab9-4126-47d3-a4b2-1c60f18ab779" }, "source": [ "from transformers import pipeline\n", "text_generation = pipeline(\"text-generation\")\n", "set_seed(31)" ], "execution_count": 3, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "No model was supplied, defaulted to gpt2 (https://huggingface.co/gpt2)\n" ] }, { "output_type": "display_data", "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "7cacdaa166a54684950b1c375f4bb4ae", "version_minor": 0, "version_major": 2 }, "text/plain": [ "Downloading: 0%| | 0.00/665 [00:00 2000:\n", "# topic_summary = topic_summary[:2000]\n", "word_list = topic_summary.split()\n", "topic_summary_len = len(topic_summary)\n", "no_of_words = len(word_list)\n", "inputs_len = get_inputs_length(topic_summary)\n", "print(f\"Topic Summary: {topic_summary}\")\n", "print(f\"Topic Summary Length: {topic_summary_len}\")\n", "print(f\"No of Words in Summary: {no_of_words}\")\n", "print(f\"Length of Input IDs: {inputs_len}\")\n", "\n", "# starting_words = [[\"That\", \"Had\", \"Not\", \"But\", \"That\"], \n", "# [\"There\", \"Who\", \"She\", \"Tormenting\", \"Til\"],\n", "# [\"Relentless\", \"This\", \"First\", \"and\", \"then\"],\n", "# [\"There\", \"Who\", \"That\", \"To\", \"She\"],\n", "# [\"There\", \"Who\", \"Two\", \"Four\", \"Have\"]]\n", "\n", "starting_words = [\"That\", \"Had\", \"Not\", \"But\", \"With\", \"I\", \"Because\", \"There\", \"Who\", \"She\", \"He\", \"To\", \"Whose\", \"In\", \"And\", \"When\", \"Or\", \"So\", \"The\", \"Of\", \"Every\", \"Whom\"]\n", "\n", "# rhyming_words = [[\"told\", \"bold\", \"woodchuck\", \"truck\", \"road\"], \n", "# [\"Nice\", \"grease\", \"house\", \"spouse\", \"peace\"],\n", "# [\"deadlines\", \"lines\", \"edits\", \"credits\", \"wine\"],\n", "# [\"Lynn\", \"thin\", \"essayed\", \"lemonade\", \"in\"],\n", "# [\"beard\", \"feared\", \"hen\", \"wren\", \"beard\"]] \n", "\n", "for i in range(5):\n", " rhyming_words = []\n", " while len(rhyming_words) < 5:\n", " first_line = text_generation(topic_summary + \" \" + random.choice(starting_words), max_length=inputs_len + 9, do_sample=False, return_full_text=False)[0]['generated_text']\n", " print(f\"First Line: {first_line}\")\n", " rhyming_words = pronouncing.rhymes(first_line.split()[-1]) \n", " print(rhyming_words)\n", " limerick = first_line + \"\\n\"\n", "\n", " for j in range(4):\n", " #gpt2_sentence = text_generation(topic_summary + \" \" + starting_words[i][j], max_length=no_of_words + 4, do_sample=False)[0]\n", " gpt2_sentence = text_generation(topic_summary + \" \" + random.choice(starting_words), max_length=inputs_len + 3, do_sample=False, return_full_text=False)[0]\n", " #sentence = gpt2_sentence['generated_text'] + \" ___ ___ ___ \" + rhyming_words[i][j]\n", " sentence = gpt2_sentence['generated_text'] + \" ___ ___ ___ \" + rhyming_words[j]\n", " print(\"Original Sentence: \", sentence)\n", " sentence = sentence.replace(\"___\",\"\")\n", " print(\"Original Sentence replaced with mask: \", sentence)\n", " print(\"\\n\")\n", " \n", " predicted_blanks = get_prediction(sentence)\n", " print(\"\\nBest guess for fill in the blank: \", predicted_blanks)\n", " limerick = limerick + gpt2_sentence['generated_text'] + predicted_blanks + \" \" + rhyming_words[j] + \"\\n\"\n", "\n", " limericks.append(limerick)\n", "\n", "print(\"\\n\")\n", "print(f\"Generated {len(limericks)} limericks: \\n\")\n", "for limerick in limericks:\n", " print(limerick)" ], "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "No model was supplied, defaulted to gpt2 (https://huggingface.co/gpt2)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Please enter a topic: Association football\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Topic Summary: Association football more commonly known as simply football or soccer is a team sport played with a spherical ball between two teams of 11 players It is played by approximately 250 million players in over 200 countries and dependencies making it the worlds most popular sport The game is played on a rectangular field called a pitch with a goal at each end The object of the game is to score more goals than the opposition by moving the ball beyond the goal line into the opposing goal usually within a time frame of 90 or more minutes\n", "Football is played in accordance with a set of rules known as the Laws of the Game The ball is 6870 cm 2728 in in circumference and known as the football The two teams compete to get the ball into the other teams goal between the posts and under the bar thereby scoring a goal Players are not allowed to touch the ball with hands or arms while it is in play except for the goalkeepers within the penalty area Players may use any other part of their body to strike or pass the ball and mainly use their feet The team that scores more goals at the end of the game is the winner if both teams have scored an equal number of goals either a draw is declared or the game goes into extra time or a penalty shootout depending on the format of the competition Each team is led by a captain who has only one official responsibility as mandated by the Laws of the Game to represent their team in the coin toss prior to kickoff or penalty kicksFootball is governed internationally by the International Federation of Association Football FIFA French Fédération Internationale de Football Association which organises World Cups for men and women every four years The mens FIFA World Cup has taken place every four years since 1930 with the exception of 1942 and 1946 tournaments which were cancelled due to World War II Approximately 190200 national teams compete in qualifying tournaments within the scope of continental confederations for a place in the finals The finals tournament is held every four years and involves 32 national teams competing over four weeks It is the most prestigious mens football tournament in the world and the most widely viewed and followed sporting event in the world exceeding the Olympic Games Similarly the FIFA Womens World Cup has been played every four years since 1991 though football has been played by women since it has existed A recordbreaking 112 billion viewers watched the 2019 FIFA Womens World Cup in FranceThe most prestigious competitions in European club football are the UEFA Champions League and UEFA Womens Champions League which attract an extensive television audience throughout the world The final of the mens tournament has been in recent years the mostwatched annual sporting event in the world The top five European mens leagues are the Premier League England La Liga Spain Bundesliga Germany Serie A Italy and Ligue 1 France Attracting most of the worlds best players each of the leagues has a total wage cost in excess of 600 million763 millionUS1185 billion\n", "Topic Summary Length: 3043\n", "No of Words in Summary: 532\n", "Length of Input IDs: 568\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: the world's top 10 mens leagues\n", "['fatigues', 'intrigues', \"league's\", \"leagues'\", 'tiegs']\n", "Original Sentence: the world ___ ___ ___ fatigues\n", "Original Sentence replaced with mask: the world fatigues\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : [\"'s\", 'of', 'in', 'needs', 'is']\n", "Mask 2 Guesses : ['the', 'wear', 'best', 'most', 'wearing']\n", "Mask 3 Guesses : ['military', 'of', 'combat', 'war', 'army']\n", "\n", "Best guess for fill in the blank: 's the military\n", "Original Sentence: far the ___ ___ ___ intrigues\n", "Original Sentence replaced with mask: far the intrigues\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['politics', 'dark', 'world', 'shadows', 'middle']\n", "Mask 2 Guesses : ['of', 'and', '-', ':', ',']\n", "Mask 3 Guesses : ['the', 'and', 'political', 'palace', 'of']\n", "\n", "Best guess for fill in the blank: politics of the\n", "Original Sentence: is the ___ ___ ___ league's\n", "Original Sentence replaced with mask: is the league's\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['top', 'best', 'most', 'biggest', 'rest']\n", "Mask 2 Guesses : ['of', 'is', 'and', 'in', 'are']\n", "Mask 3 Guesses : ['the', 'of', 'this', 'in', 'rugby']\n", "\n", "Best guess for fill in the blank: top of the\n", "Original Sentence: the World ___ ___ ___ leagues'\n", "Original Sentence replaced with mask: the World leagues'\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['Cup', \"'s\", 'League', 'Championship', 'Series']\n", "Mask 2 Guesses : [\"'\", 'top', \"'s\", 'best', 'the']\n", "Mask 3 Guesses : ['top', 'best', 'fantasy', 'top', 'rugby']\n", "\n", "Best guess for fill in the blank: Cup ' top\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: are the most popular players in the\n", "[]\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: more than the entire US$1.\n", "[]\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: aded by the United States of America,\n", "[]\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: be eligible for the 2018 FIFA World Cup\n", "['bupp', 'chupp', 'closeup', 'cup', 'cupp', 'grupp', 'hupp', 'knupp', 'krupp', 'lay-up', 'pup', 'rupp', 'ruppe', 'schlup', 'schrupp', 'schupp', 'shupp', 'strupp', 'stupp', 'sup', 'trupp', 'up', 'upp', 'yup']\n", "Original Sentence: ets of ___ ___ ___ bupp\n", "Original Sentence replaced with mask: ets of bupp\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['the', 'bu', 'a', 'p', 'b']\n", "Mask 2 Guesses : ['', 'p', 'and', 'k', 'pp']\n", "Mask 3 Guesses : ['of', 'the', 'and', 'in', ':']\n", "\n", "Best guess for fill in the blank: the of\n", "Original Sentence: the exception ___ ___ ___ chupp\n", "Original Sentence replaced with mask: the exception chupp\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['is', ':', 'to', 'of', ',']\n", "Mask 2 Guesses : ['the', 'ch', '', 'a', ':']\n", "Mask 3 Guesses : [':', 'and', '.', 'the', ',']\n", "\n", "Best guess for fill in the blank: is the :\n", "Original Sentence: the exception ___ ___ ___ closeup\n", "Original Sentence replaced with mask: the exception closeup\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['to', 'of', ':', 'is', '']\n", "Mask 2 Guesses : ['the', 'a', 'this', '', 'an']\n", "Mask 3 Guesses : [':', 'in', 'final', 'a', 'the']\n", "\n", "Best guess for fill in the blank: to the :\n", "Original Sentence: of the ___ ___ ___ cup\n", "Original Sentence replaced with mask: of the cup\n", "\n", "\n", "Mask 1 Guesses : ['cup', '', 'd', 'l', 'cups']\n", "Mask 2 Guesses : ['of', '-', 'in', '', 'and']\n", "Mask 3 Guesses : ['the', 'coffee', 'a', 'tea', 'o']" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "\n", "Best guess for fill in the blank: cup of the\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: only is the world's largest football league\n", "['creagh', 'deeg', 'eeg', 'fatigue', 'feig', 'fleig', 'greig', 'heeg', 'intrigue', 'killeagh', 'klieg', 'kreig', 'krieg', 'mckeag', 'mckeague', 'mctigue', 'pigue', 'reeg', 'rieg', 'schmieg', 'sieg', 'steeg', 'steig', 'stieg', 'teague', 'teig', 'tigue', 'vigue', 'zieg', 'zwieg']\n", "Original Sentence: are over ___ ___ ___ creagh\n", "Original Sentence replaced with mask: are over creagh\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['the', 'to', 'a', 'here', ',']\n", "Mask 2 Guesses : ['', 'the', ',', ':', 'o']\n", "Mask 3 Guesses : ['the', ':', 'in', 'of', ',']\n", "\n", "Best guess for fill in the blank: the the\n", "Original Sentence: the exception ___ ___ ___ deeg\n", "Original Sentence replaced with mask: the exception deeg\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['of', 'is', 'to', ':', 'being']\n", "Mask 2 Guesses : ['the', 'a', '', 'that', ':']\n", "Mask 3 Guesses : ['the', ':', '.', 'and', 'of']\n", "\n", "Best guess for fill in the blank: of the the\n", "Original Sentence: year the ___ ___ ___ eeg\n", "Original Sentence replaced with mask: year the eeg\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['e', 'd', 'f', 'g', 'k']\n", "Mask 2 Guesses : ['e', 'of', ',', 'd', 'e']\n", "Mask 3 Guesses : ['der', 'en', 'e', ',', ':']\n", "\n", "Best guess for fill in the blank: e e der\n", "Original Sentence: more than ___ ___ ___ fatigue\n", "Original Sentence replaced with mask: more than fatigue\n", "\n", "\n", "Mask 1 Guesses : ['a', 'just', 'one', 'the', 'usual']\n", "Mask 2 Guesses : ['signs', '-', 'days', 'hours', 'case']\n", "Mask 3 Guesses : ['of', 'and', 'with', 'chronic', ':']\n", "\n", "Best guess for fill in the blank: a signs of\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n", "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: the exception of the US, the world\n", "['curled', 'hurled', 'neworld', 'neworld', 'swirled', 'transworld', 'twirled', 'unfurled', 'whirled', 'whirled']\n", "Original Sentence: is the ___ ___ ___ curled\n", "Original Sentence replaced with mask: is the curled\n", "\n", "\n", "Mask 1 Guesses : ['hair', 'curl', 'cat', 'ball', 'dog']\n", "Mask 2 Guesses : ['is', 'can', 'has', 'to', 'are']\n", "Mask 3 Guesses : ['be', 'is', 'are', 'been', 'get']\n", "\n", "Best guess for fill in the blank: hair is be\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n", "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Original Sentence: team ___ ___ ___ hurled\n", "Original Sentence replaced with mask: team hurled\n", "\n", "\n", "Mask 1 Guesses : ['', ':', 'of', 'the', '-']\n", "Mask 2 Guesses : ['of', 'the', '', 'have', 'that']\n", "Mask 3 Guesses : ['were', 'been', 'insults', 'be', 'was']\n", "\n", "Best guess for fill in the blank: of were\n", "Original Sentence: year the ___ ___ ___ neworld\n", "Original Sentence replaced with mask: year the neworld\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['best', 'new', 'world', 'top', '']\n", "Mask 2 Guesses : ['of', '', 'and', ',', ':']\n", "Mask 3 Guesses : ['of', 'the', 'at', 'in', ':']\n", "\n", "Best guess for fill in the blank: best of of\n", "Original Sentence: the world ___ ___ ___ neworld\n", "Original Sentence replaced with mask: the world neworld\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['of', 'is', ',', \"'s\", '']\n", "Mask 2 Guesses : ['the', 'a', 'of', 'on', '']\n", "Mask 3 Guesses : ['the', 'and', ',', 'a', 's']\n", "\n", "Best guess for fill in the blank: of the the\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: world's most successful football team is the\n", "[]\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: the World Cup in Brazil in 1992,\n", "[]\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "First Line: the most successful European mens league is\n", "[\"'tis\", 'biz', 'buis', 'chandeliers', 'czyz', 'fizz', 'frizz', 'griz', 'his', 'kriz', 'liz', 'ms', 'ms.', 'quiz', 'riz', 'says', \"shultz's\", 'tis', 'whiz', 'whiz', 'wiz', 'wiz']\n", "Original Sentence: of the ___ ___ ___ 'tis\n", "Original Sentence replaced with mask: of the 'tis\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['world', 'same', 'time', 'day', 'year']\n", "Mask 2 Guesses : [',', '', 'that', 'and', 'of']\n", "Mask 3 Guesses : ['here', 'as', 'Here', 'how', ',']\n", "\n", "Best guess for fill in the blank: world , here\n", "Original Sentence: aded by ___ ___ ___ biz\n", "Original Sentence replaced with mask: aded by biz\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : [':', 'the', '', 'j', 'r']\n", "Mask 2 Guesses : ['', 'in', ':', 'from', 'at']\n", "Mask 3 Guesses : ['the', ',', 'iz', 'biz', 'in']\n", "\n", "Best guess for fill in the blank: : the\n", "Original Sentence: the exception ___ ___ ___ buis\n", "Original Sentence replaced with mask: the exception buis\n", "\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Mask 1 Guesses : ['to', ':', 'of', 'is', '']\n", "Mask 2 Guesses : ['the', 'le', 'c', 'de', 'la']\n", "Mask 3 Guesses : ['les', 'is', 'de', 'des', 'le']\n", "\n", "Best guess for fill in the blank: to the les\n", "Original Sentence: far the ___ ___ ___ chandeliers\n", "Original Sentence replaced with mask: far the chandeliers\n", "\n", "\n", "Mask 1 Guesses : ['world', 'light', 'rise', 'glass', 'power']\n", "Mask 2 Guesses : ['of', ':', '-', 'and', ',']\n", "Mask 3 Guesses : ['the', 'of', 'and', 'crystal', 'glass']\n", "\n", "Best guess for fill in the blank: world of the\n", "\n", "\n", "Generated 5 limericks: \n", "\n", " the world's top 10 mens leagues\n", " the world 's the military fatigues\n", " far the politics of the intrigues\n", " is the top of the league's\n", " the World Cup ' top leagues'\n", "\n", " be eligible for the 2018 FIFA World Cup\n", "ets of the of bupp\n", " the exception is the : chupp\n", " the exception to the : closeup\n", " of the cup of the cup\n", "\n", " only is the world's largest football league\n", " are over the the creagh\n", " the exception of the the deeg\n", " year the e e der eeg\n", " more than a signs of fatigue\n", "\n", " the exception of the US, the world\n", " is the hair is be curled\n", " team of were hurled\n", " year the best of of neworld\n", " the world of the the neworld\n", "\n", " the most successful European mens league is\n", " of the world , here 'tis\n", "aded by : the biz\n", " the exception to the les buis\n", " far the world of the chandeliers\n", "\n" ] } ] } ] }