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tfjs-models/qna at master · tensorflow/tfjs-models · GitHub
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class=\"markdown-body entry-content container-lg\" itemprop=\"text\"\u003e\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch1 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eQuestion and Answer\u003c/h1\u003e\u003ca id=\"user-content-question-and-answer\" class=\"anchor\" aria-label=\"Permalink: Question and Answer\" href=\"#question-and-answer\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eUse a pre-trained model to answer questions based on the content of a given passage.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eHow it works\u003c/h3\u003e\u003ca id=\"user-content-how-it-works\" class=\"anchor\" aria-label=\"Permalink: How it works\" href=\"#how-it-works\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe model can be used to build a system that can answer users’ questions in natural language. It was created using a pre-trained BERT model fine-tuned on \u003ca href=\"https://rajpurkar.github.io/SQuAD-explorer/\" rel=\"nofollow\"\u003eSQuAD 2.0 dataset\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca href=\"https://github.com/google-research/bert\"\u003eBERT\u003c/a\u003e, or Bidirectional Encoder Representations from Transformers, is a method of pre-training language representations which obtains state-of-the-art results on a wide array of Natural Language Processing tasks.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThis app uses a compressed version of BERT, \u003ca href=\"https://openreview.net/forum?id=SJxjVaNKwB\" rel=\"nofollow\"\u003eMobileBERT\u003c/a\u003e, that runs 4x faster and has 4x smaller model size.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca href=\"https://rajpurkar.github.io/SQuAD-explorer/\" rel=\"nofollow\"\u003eSQuAD\u003c/a\u003e, or Stanford Question Answering Dataset, is a reading comprehension dataset consisting of articles from Wikipedia and a set of question-answer pairs for each article.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe model takes a passage and a question as input, then returns a segment of the passage that most likely answers the question. It requires semi-complex pre-processing including tokenization and post-processing steps that are described in the BERT \u003ca href=\"https://arxiv.org/abs/1810.04805\" rel=\"nofollow\"\u003epaper\u003c/a\u003e and implemented in the sample app. This model is also available in \u003ca href=\"https://www.tensorflow.org/lite/models/bert_qa/overview\" rel=\"nofollow\"\u003eTFLite\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eUsage\u003c/h2\u003e\u003ca id=\"user-content-usage\" class=\"anchor\" aria-label=\"Permalink: Usage\" href=\"#usage\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThere are two main ways to get this model in your JavaScript project: via script tags or by installing it from NPM and using a build tool like Parcel, WebPack, or Rollup.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003evia Script Tag\u003c/h3\u003e\u003ca id=\"user-content-via-script-tag\" class=\"anchor\" aria-label=\"Permalink: via Script Tag\" href=\"#via-script-tag\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"highlight highlight-text-html-basic notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"\u0026lt;!-- Make sure your page supports utf-8 characterset. --\u0026gt;\n\u0026lt;meta http-equiv=\u0026quot;Content-Type\u0026quot; content=\u0026quot;text/html; charset=UTF-8\u0026quot;\u0026gt;\n\u0026lt;!-- Load TensorFlow.js. This is required to use the qna model. --\u0026gt;\n\u0026lt;script src=\u0026quot;https://cdn.jsdelivr.net/npm/@tensorflow/tfjs\u0026quot;\u0026gt; \u0026lt;/script\u0026gt;\n\u0026lt;!-- Load the qna model. --\u0026gt;\n\u0026lt;script src=\u0026quot;https://cdn.jsdelivr.net/npm/@tensorflow-models/qna\u0026quot;\u0026gt; \u0026lt;/script\u0026gt;\n\n\u0026lt;!-- Place your code in the script tag below. You can also use an external .js file --\u0026gt;\n\u0026lt;script\u0026gt;\n // Notice there is no 'import' statement. 'qna' and 'tf' is\n // available on the index-page because of the script tag above.\n\n // Load the model.\n qna.load().then(model =\u0026gt; {\n // Find the answers\n model.findAnswers(question, passage).then(answers =\u0026gt; {\n console.log('Answers: ', answers);\n });\n });\n\u0026lt;/script\u0026gt;\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e\u0026lt;!-- Make sure your page supports utf-8 characterset. --\u0026gt;\u003c/span\u003e\n\u003cspan class=\"pl-kos\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003emeta\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003ehttp-equiv\u003c/span\u003e=\"\u003cspan class=\"pl-s\"\u003eContent-Type\u003c/span\u003e\" \u003cspan class=\"pl-c1\"\u003econtent\u003c/span\u003e=\"\u003cspan class=\"pl-s\"\u003etext/html; charset=UTF-8\u003c/span\u003e\"\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e\u0026lt;!-- Load TensorFlow.js. This is required to use the qna model. --\u0026gt;\u003c/span\u003e\n\u003cspan class=\"pl-kos\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003escript\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003esrc\u003c/span\u003e=\"\u003cspan class=\"pl-s\"\u003ehttps://cdn.jsdelivr.net/npm/@tensorflow/tfjs\u003c/span\u003e\"\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e \u003cspan class=\"pl-kos\"\u003e\u0026lt;/\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003escript\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e\u0026lt;!-- Load the qna model. --\u0026gt;\u003c/span\u003e\n\u003cspan class=\"pl-kos\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003escript\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003esrc\u003c/span\u003e=\"\u003cspan class=\"pl-s\"\u003ehttps://cdn.jsdelivr.net/npm/@tensorflow-models/qna\u003c/span\u003e\"\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e \u003cspan class=\"pl-kos\"\u003e\u0026lt;/\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003escript\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e\n\n\u003cspan class=\"pl-c\"\u003e\u0026lt;!-- Place your code in the script tag below. You can also use an external .js file --\u0026gt;\u003c/span\u003e\n\u003cspan class=\"pl-kos\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003escript\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e// Notice there is no 'import' statement. 'qna' and 'tf' is\u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e// available on the index-page because of the script tag above.\u003c/span\u003e\n\n \u003cspan class=\"pl-c\"\u003e// Load the model.\u003c/span\u003e\n \u003cspan class=\"pl-s1\"\u003eqna\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003eload\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003ethen\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u0026gt;\u003c/span\u003e \u003cspan class=\"pl-kos\"\u003e{\u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e// Find the answers\u003c/span\u003e\n \u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003efindAnswers\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003equestion\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epassage\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003ethen\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003eanswers\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u0026gt;\u003c/span\u003e \u003cspan class=\"pl-kos\"\u003e{\u003c/span\u003e\n \u003cspan class=\"pl-smi\"\u003econsole\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003elog\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e'Answers: '\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eanswers\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n \u003cspan class=\"pl-kos\"\u003e}\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n \u003cspan class=\"pl-kos\"\u003e}\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\u003cspan class=\"pl-kos\"\u003e\u0026lt;/\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003escript\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003evia NPM\u003c/h3\u003e\u003ca id=\"user-content-via-npm\" class=\"anchor\" aria-label=\"Permalink: via NPM\" href=\"#via-npm\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"highlight highlight-source-js notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"// Note: you do not need to import @tensorflow/tfjs here, but make sure you have installed the peer dependencies for tfjs-core and tfjs-converter.\n\nconst qna = require('@tensorflow-models/qna');\n\n// Load the model.\nconst model = await qna.load();\n\n// Finding the answers\nconst answers = await model.findAnswers(question, passage);\n\nconsole.log('Answers: ');\nconsole.log(answers);\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e// Note: you do not need to import @tensorflow/tfjs here, but make sure you have installed the peer dependencies for tfjs-core and tfjs-converter.\u003c/span\u003e\n\n\u003cspan class=\"pl-k\"\u003econst\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eqna\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-en\"\u003erequire\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e'@tensorflow-models/qna'\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\n\u003cspan class=\"pl-c\"\u003e// Load the model.\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003econst\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-k\"\u003eawait\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eqna\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003eload\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\n\u003cspan class=\"pl-c\"\u003e// Finding the answers\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003econst\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eanswers\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-k\"\u003eawait\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003efindAnswers\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003equestion\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epassage\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\n\u003cspan class=\"pl-smi\"\u003econsole\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003elog\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e'Answers: '\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\u003cspan class=\"pl-smi\"\u003econsole\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003elog\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003eanswers\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca href=\"https://storage.googleapis.com/tfjs-models/demos/mobilebert-qna/index.html\" rel=\"nofollow\"\u003eTry the demo here!\u003c/a\u003e\nYou can also take a look at the source code of the \u003ca href=\"/tensorflow/tfjs-models/blob/master/qna/demo\"\u003edemo app\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eNote\u003c/h3\u003e\u003ca id=\"user-content-note\" class=\"anchor\" aria-label=\"Permalink: Note\" href=\"#note\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003ePlease make sure your web page supports utf-8 character set. To achieve that you can add following line to your page:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-text-html-basic notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\" \u0026lt;meta http-equiv=\u0026quot;Content-Type\u0026quot; content=\u0026quot;text/html; charset=UTF-8\u0026quot;\u0026gt;\"\u003e\u003cpre\u003e \u003cspan class=\"pl-kos\"\u003e\u0026lt;\u003c/span\u003e\u003cspan class=\"pl-ent\"\u003emeta\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003ehttp-equiv\u003c/span\u003e=\"\u003cspan class=\"pl-s\"\u003eContent-Type\u003c/span\u003e\" \u003cspan class=\"pl-c1\"\u003econtent\u003c/span\u003e=\"\u003cspan class=\"pl-s\"\u003etext/html; charset=UTF-8\u003c/span\u003e\"\u003cspan class=\"pl-kos\"\u003e\u0026gt;\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eAPI\u003c/h2\u003e\u003ca id=\"user-content-api\" class=\"anchor\" aria-label=\"Permalink: API\" href=\"#api\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch4 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eLoading the model\u003c/h4\u003e\u003ca id=\"user-content-loading-the-model\" class=\"anchor\" aria-label=\"Permalink: Loading the model\" href=\"#loading-the-model\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eWhen using a script tag, the package is available as \u003ccode\u003eqna\u003c/code\u003e in the global namespace.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-js notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"// you can load the model without providing the config object.\nmodel = await qna.load();\n// or you can specify the model url.\nconfig = {modelUrl: 'https://yourown-server/qna/model.json'};\ncustomModel = await qna.load(config);\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e// you can load the model without providing the config object.\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-k\"\u003eawait\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eqna\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003eload\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e// or you can specify the model url.\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003econfig\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-kos\"\u003e{\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003emodelUrl\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'https://yourown-server/qna/model.json'\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e}\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003ecustomModel\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-k\"\u003eawait\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eqna\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003eload\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003econfig\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eArgs:\n\u003cstrong\u003econfig\u003c/strong\u003e Model Config structure with following attributes:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003cstrong\u003emodelUrl:\u003c/strong\u003e An optional string that specifies custom url of the model. This is useful for area/countries that don't have access to the model hosted on GCP.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003eReturns a \u003ccode\u003emodel\u003c/code\u003e object.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch4 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eFind the answers\u003c/h4\u003e\u003ca id=\"user-content-find-the-answers\" class=\"anchor\" aria-label=\"Permalink: Find the answers\" href=\"#find-the-answers\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eYou can find the answers for a given question and associated passage with the model without needing to create a Tensor.\n\u003ccode\u003emodel.findAnswers\u003c/code\u003e takes two inputs (question and passage) and returns an array of answers ranked by their scores.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThis method exists on the model that is loaded from \u003ccode\u003eqna.load()\u003c/code\u003e.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-js notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"model.findAnswers(\n question: string, passage: string\n)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003efindAnswers\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\n \u003cspan class=\"pl-s1\"\u003equestion\u003c/span\u003e: \u003cspan class=\"pl-s1\"\u003estring\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epassage\u003c/span\u003e: \u003cspan class=\"pl-s1\"\u003estring\u003c/span\u003e\n\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eArgs:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003cstrong\u003equestion:\u003c/strong\u003e The question string.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003epassage:\u003c/strong\u003e The content to extract answers from.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003eReturns an Promise of array of answers that look like following:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-js notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"[{\n text: \u0026quot;Sundar Pichai\u0026quot;,\n startIndex: 1143,\n endIndex: 1156,\n score: 0.8380282521247864\n}]\"\u003e\u003cpre\u003e\u003cspan class=\"pl-kos\"\u003e[\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e{\u003c/span\u003e\n \u003cspan class=\"pl-c1\"\u003etext\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Sundar Pichai\"\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e\n \u003cspan class=\"pl-c1\"\u003estartIndex\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e1143\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e\n \u003cspan class=\"pl-c1\"\u003eendIndex\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e1156\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e\n \u003cspan class=\"pl-c1\"\u003escore\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e0.8380282521247864\u003c/span\u003e\n\u003cspan class=\"pl-kos\"\u003e}\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e]\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eIn which the \u003ccode\u003etext\u003c/code\u003e is of string type and represents the answer body, and \u003ccode\u003escore\u003c/code\u003e is a number, indicates the confident level. The \u003ccode\u003estartIndex\u003c/code\u003e is the index of the starting character of the answer in the passage. The \u003ccode\u003eendIndex\u003c/code\u003e is index of the last character of the answer.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eHere is an example run of the QnA model:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-js notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"const passage = \u0026quot;Google LLC is an American multinational technology company that specializes in Internet-related services and products, which include online advertising technologies, search engine, cloud computing, software, and hardware. It is considered one of the Big Four technology companies, alongside Amazon, Apple, and Facebook. Google was founded in September 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University in California. Together they own about 14 percent of its shares and control 56 percent of the stockholder voting power through supervoting stock. They incorporated Google as a California privately held company on September 4, 1998, in California. Google was then reincorporated in Delaware on October 22, 2002. An initial public offering (IPO) took place on August 19, 2004, and Google moved to its headquarters in Mountain View, California, nicknamed the Googleplex. In August 2015, Google announced plans to reorganize its various interests as a conglomerate called Alphabet Inc. Google is Alphabet's leading subsidiary and will continue to be the umbrella company for Alphabet's Internet interests. Sundar Pichai was appointed CEO of Google, replacing Larry Page who became the CEO of Alphabet.\u0026quot;\nconst question = \u0026quot;Who is the CEO of Google?\u0026quot;\nconst model = await qna.load();\nconst answers = await model.findAnswers(question, passage);\nconsole.log(answers);\n/**\n[{\n text: \u0026quot;Sundar Pichai\u0026quot;,\n startIndex: 1143,\n endIndex: 1156,\n score: 0.8380282521247864\n}]\n**/\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003econst\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epassage\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s\"\u003e\"Google LLC is an American multinational technology company that specializes in Internet-related services and products, which include online advertising technologies, search engine, cloud computing, software, and hardware. It is considered one of the Big Four technology companies, alongside Amazon, Apple, and Facebook. Google was founded in September 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University in California. Together they own about 14 percent of its shares and control 56 percent of the stockholder voting power through supervoting stock. They incorporated Google as a California privately held company on September 4, 1998, in California. Google was then reincorporated in Delaware on October 22, 2002. An initial public offering (IPO) took place on August 19, 2004, and Google moved to its headquarters in Mountain View, California, nicknamed the Googleplex. In August 2015, Google announced plans to reorganize its various interests as a conglomerate called Alphabet Inc. Google is Alphabet's leading subsidiary and will continue to be the umbrella company for Alphabet's Internet interests. Sundar Pichai was appointed CEO of Google, replacing Larry Page who became the CEO of Alphabet.\"\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003econst\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003equestion\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s\"\u003e\"Who is the CEO of Google?\"\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003econst\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-k\"\u003eawait\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eqna\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003eload\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003econst\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eanswers\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-k\"\u003eawait\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003efindAnswers\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003equestion\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e,\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epassage\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\u003cspan class=\"pl-smi\"\u003econsole\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e.\u003c/span\u003e\u003cspan class=\"pl-en\"\u003elog\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e(\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003eanswers\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e)\u003c/span\u003e\u003cspan class=\"pl-kos\"\u003e;\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e/**\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e[{\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e text: \"Sundar Pichai\",\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e startIndex: 1143,\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e endIndex: 1156,\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e score: 0.8380282521247864\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e}]\u003c/span\u003e\n\u003cspan class=\"pl-c\"\u003e**/\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003c/article\u003e","errorMessage":null,"headerInfo":{"toc":[{"level":1,"text":"Question and Answer","anchor":"question-and-answer","htmlText":"Question and Answer"},{"level":3,"text":"How it works","anchor":"how-it-works","htmlText":"How it works"},{"level":2,"text":"Usage","anchor":"usage","htmlText":"Usage"},{"level":3,"text":"via Script Tag","anchor":"via-script-tag","htmlText":"via Script Tag"},{"level":3,"text":"via NPM","anchor":"via-npm","htmlText":"via NPM"},{"level":3,"text":"Note","anchor":"note","htmlText":"Note"},{"level":2,"text":"API","anchor":"api","htmlText":"API"},{"level":4,"text":"Loading the model","anchor":"loading-the-model","htmlText":"Loading the model"},{"level":4,"text":"Find the answers","anchor":"find-the-answers","htmlText":"Find the 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1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Use a pre-trained model to answer questions based on the content of a given passage.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">How it works</h3><a id="user-content-how-it-works" class="anchor" aria-label="Permalink: How it works" href="#how-it-works"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">The model can be used to build a system that can answer users’ questions in natural language. It was created using a pre-trained BERT model fine-tuned on <a href="https://rajpurkar.github.io/SQuAD-explorer/" rel="nofollow">SQuAD 2.0 dataset</a>.</p> <p dir="auto"><a href="https://github.com/google-research/bert">BERT</a>, or Bidirectional Encoder Representations from Transformers, is a method of pre-training language representations which obtains state-of-the-art results on a wide array of Natural Language Processing tasks.</p> <p dir="auto">This app uses a compressed version of BERT, <a href="https://openreview.net/forum?id=SJxjVaNKwB" rel="nofollow">MobileBERT</a>, that runs 4x faster and has 4x smaller model size.</p> <p dir="auto"><a href="https://rajpurkar.github.io/SQuAD-explorer/" rel="nofollow">SQuAD</a>, or Stanford Question Answering Dataset, is a reading comprehension dataset consisting of articles from Wikipedia and a set of question-answer pairs for each article.</p> <p dir="auto">The model takes a passage and a question as input, then returns a segment of the passage that most likely answers the question. It requires semi-complex pre-processing including tokenization and post-processing steps that are described in the BERT <a href="https://arxiv.org/abs/1810.04805" rel="nofollow">paper</a> and implemented in the sample app. This model is also available in <a href="https://www.tensorflow.org/lite/models/bert_qa/overview" rel="nofollow">TFLite</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Usage</h2><a id="user-content-usage" class="anchor" aria-label="Permalink: Usage" href="#usage"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">There are two main ways to get this model in your JavaScript project: via script tags or by installing it from NPM and using a build tool like Parcel, WebPack, or Rollup.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">via Script Tag</h3><a id="user-content-via-script-tag" class="anchor" aria-label="Permalink: via Script Tag" href="#via-script-tag"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="highlight highlight-text-html-basic notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="<!-- Make sure your page supports utf-8 characterset. --> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <!-- Load TensorFlow.js. This is required to use the qna model. --> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"> </script> <!-- Load the qna model. --> <script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/qna"> </script> <!-- Place your code in the script tag below. You can also use an external .js file --> <script> // Notice there is no 'import' statement. 'qna' and 'tf' is // available on the index-page because of the script tag above. // Load the model. qna.load().then(model => { // Find the answers model.findAnswers(question, passage).then(answers => { console.log('Answers: ', answers); }); }); </script>"><pre><span class="pl-c"><!-- Make sure your page supports utf-8 characterset. --></span> <span class="pl-kos"><</span><span class="pl-ent">meta</span> <span class="pl-c1">http-equiv</span>="<span class="pl-s">Content-Type</span>" <span class="pl-c1">content</span>="<span class="pl-s">text/html; charset=UTF-8</span>"<span class="pl-kos">></span> <span class="pl-c"><!-- Load TensorFlow.js. This is required to use the qna model. --></span> <span class="pl-kos"><</span><span class="pl-ent">script</span> <span class="pl-c1">src</span>="<span class="pl-s">https://cdn.jsdelivr.net/npm/@tensorflow/tfjs</span>"<span class="pl-kos">></span> <span class="pl-kos"></</span><span class="pl-ent">script</span><span class="pl-kos">></span> <span class="pl-c"><!-- Load the qna model. --></span> <span class="pl-kos"><</span><span class="pl-ent">script</span> <span class="pl-c1">src</span>="<span class="pl-s">https://cdn.jsdelivr.net/npm/@tensorflow-models/qna</span>"<span class="pl-kos">></span> <span class="pl-kos"></</span><span class="pl-ent">script</span><span class="pl-kos">></span> <span class="pl-c"><!-- Place your code in the script tag below. You can also use an external .js file --></span> <span class="pl-kos"><</span><span class="pl-ent">script</span><span class="pl-kos">></span> <span class="pl-c">// Notice there is no 'import' statement. 'qna' and 'tf' is</span> <span class="pl-c">// available on the index-page because of the script tag above.</span> <span class="pl-c">// Load the model.</span> <span class="pl-s1">qna</span><span class="pl-kos">.</span><span class="pl-en">load</span><span class="pl-kos">(</span><span class="pl-kos">)</span><span class="pl-kos">.</span><span class="pl-en">then</span><span class="pl-kos">(</span><span class="pl-s1">model</span> <span class="pl-c1">=></span> <span class="pl-kos">{</span> <span class="pl-c">// Find the answers</span> <span class="pl-s1">model</span><span class="pl-kos">.</span><span class="pl-en">findAnswers</span><span class="pl-kos">(</span><span class="pl-s1">question</span><span class="pl-kos">,</span> <span class="pl-s1">passage</span><span class="pl-kos">)</span><span class="pl-kos">.</span><span class="pl-en">then</span><span class="pl-kos">(</span><span class="pl-s1">answers</span> <span class="pl-c1">=></span> <span class="pl-kos">{</span> <span class="pl-smi">console</span><span class="pl-kos">.</span><span class="pl-en">log</span><span class="pl-kos">(</span><span class="pl-s">'Answers: '</span><span class="pl-kos">,</span> <span class="pl-s1">answers</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-kos">}</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-kos">}</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-kos"></</span><span class="pl-ent">script</span><span class="pl-kos">></span></pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">via NPM</h3><a id="user-content-via-npm" class="anchor" aria-label="Permalink: via NPM" href="#via-npm"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="highlight highlight-source-js notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="// Note: you do not need to import @tensorflow/tfjs here, but make sure you have installed the peer dependencies for tfjs-core and tfjs-converter. const qna = require('@tensorflow-models/qna'); // Load the model. const model = await qna.load(); // Finding the answers const answers = await model.findAnswers(question, passage); console.log('Answers: '); console.log(answers);"><pre><span class="pl-c">// Note: you do not need to import @tensorflow/tfjs here, but make sure you have installed the peer dependencies for tfjs-core and tfjs-converter.</span> <span class="pl-k">const</span> <span class="pl-s1">qna</span> <span class="pl-c1">=</span> <span class="pl-en">require</span><span class="pl-kos">(</span><span class="pl-s">'@tensorflow-models/qna'</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-c">// Load the model.</span> <span class="pl-k">const</span> <span class="pl-s1">model</span> <span class="pl-c1">=</span> <span class="pl-k">await</span> <span class="pl-s1">qna</span><span class="pl-kos">.</span><span class="pl-en">load</span><span class="pl-kos">(</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-c">// Finding the answers</span> <span class="pl-k">const</span> <span class="pl-s1">answers</span> <span class="pl-c1">=</span> <span class="pl-k">await</span> <span class="pl-s1">model</span><span class="pl-kos">.</span><span class="pl-en">findAnswers</span><span class="pl-kos">(</span><span class="pl-s1">question</span><span class="pl-kos">,</span> <span class="pl-s1">passage</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-smi">console</span><span class="pl-kos">.</span><span class="pl-en">log</span><span class="pl-kos">(</span><span class="pl-s">'Answers: '</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-smi">console</span><span class="pl-kos">.</span><span class="pl-en">log</span><span class="pl-kos">(</span><span class="pl-s1">answers</span><span class="pl-kos">)</span><span class="pl-kos">;</span></pre></div> <p dir="auto"><a href="https://storage.googleapis.com/tfjs-models/demos/mobilebert-qna/index.html" rel="nofollow">Try the demo here!</a> You can also take a look at the source code of the <a href="/tensorflow/tfjs-models/blob/master/qna/demo">demo app</a>.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Note</h3><a id="user-content-note" class="anchor" aria-label="Permalink: Note" href="#note"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Please make sure your web page supports utf-8 character set. To achieve that you can add following line to your page:</p> <div class="highlight highlight-text-html-basic notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content=" <meta http-equiv="Content-Type" content="text/html; charset=UTF-8">"><pre> <span class="pl-kos"><</span><span class="pl-ent">meta</span> <span class="pl-c1">http-equiv</span>="<span class="pl-s">Content-Type</span>" <span class="pl-c1">content</span>="<span class="pl-s">text/html; charset=UTF-8</span>"<span class="pl-kos">></span></pre></div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">API</h2><a id="user-content-api" class="anchor" aria-label="Permalink: API" href="#api"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h4 tabindex="-1" class="heading-element" dir="auto">Loading the model</h4><a id="user-content-loading-the-model" class="anchor" aria-label="Permalink: Loading the model" href="#loading-the-model"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">When using a script tag, the package is available as <code>qna</code> in the global namespace.</p> <div class="highlight highlight-source-js notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="// you can load the model without providing the config object. model = await qna.load(); // or you can specify the model url. config = {modelUrl: 'https://yourown-server/qna/model.json'}; customModel = await qna.load(config);"><pre><span class="pl-c">// you can load the model without providing the config object.</span> <span class="pl-s1">model</span> <span class="pl-c1">=</span> <span class="pl-k">await</span> <span class="pl-s1">qna</span><span class="pl-kos">.</span><span class="pl-en">load</span><span class="pl-kos">(</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-c">// or you can specify the model url.</span> <span class="pl-s1">config</span> <span class="pl-c1">=</span> <span class="pl-kos">{</span><span class="pl-c1">modelUrl</span>: <span class="pl-s">'https://yourown-server/qna/model.json'</span><span class="pl-kos">}</span><span class="pl-kos">;</span> <span class="pl-s1">customModel</span> <span class="pl-c1">=</span> <span class="pl-k">await</span> <span class="pl-s1">qna</span><span class="pl-kos">.</span><span class="pl-en">load</span><span class="pl-kos">(</span><span class="pl-s1">config</span><span class="pl-kos">)</span><span class="pl-kos">;</span></pre></div> <p dir="auto">Args: <strong>config</strong> Model Config structure with following attributes:</p> <ul dir="auto"> <li><strong>modelUrl:</strong> An optional string that specifies custom url of the model. This is useful for area/countries that don't have access to the model hosted on GCP.</li> </ul> <p dir="auto">Returns a <code>model</code> object.</p> <div class="markdown-heading" dir="auto"><h4 tabindex="-1" class="heading-element" dir="auto">Find the answers</h4><a id="user-content-find-the-answers" class="anchor" aria-label="Permalink: Find the answers" href="#find-the-answers"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">You can find the answers for a given question and associated passage with the model without needing to create a Tensor. <code>model.findAnswers</code> takes two inputs (question and passage) and returns an array of answers ranked by their scores.</p> <p dir="auto">This method exists on the model that is loaded from <code>qna.load()</code>.</p> <div class="highlight highlight-source-js notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="model.findAnswers( question: string, passage: string )"><pre><span class="pl-s1">model</span><span class="pl-kos">.</span><span class="pl-en">findAnswers</span><span class="pl-kos">(</span> <span class="pl-s1">question</span>: <span class="pl-s1">string</span><span class="pl-kos">,</span> <span class="pl-s1">passage</span>: <span class="pl-s1">string</span> <span class="pl-kos">)</span></pre></div> <p dir="auto">Args:</p> <ul dir="auto"> <li><strong>question:</strong> The question string.</li> <li><strong>passage:</strong> The content to extract answers from.</li> </ul> <p dir="auto">Returns an Promise of array of answers that look like following:</p> <div class="highlight highlight-source-js notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="[{ text: "Sundar Pichai", startIndex: 1143, endIndex: 1156, score: 0.8380282521247864 }]"><pre><span class="pl-kos">[</span><span class="pl-kos">{</span> <span class="pl-c1">text</span>: <span class="pl-s">"Sundar Pichai"</span><span class="pl-kos">,</span> <span class="pl-c1">startIndex</span>: <span class="pl-c1">1143</span><span class="pl-kos">,</span> <span class="pl-c1">endIndex</span>: <span class="pl-c1">1156</span><span class="pl-kos">,</span> <span class="pl-c1">score</span>: <span class="pl-c1">0.8380282521247864</span> <span class="pl-kos">}</span><span class="pl-kos">]</span></pre></div> <p dir="auto">In which the <code>text</code> is of string type and represents the answer body, and <code>score</code> is a number, indicates the confident level. The <code>startIndex</code> is the index of the starting character of the answer in the passage. The <code>endIndex</code> is index of the last character of the answer.</p> <p dir="auto">Here is an example run of the QnA model:</p> <div class="highlight highlight-source-js notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="const passage = "Google LLC is an American multinational technology company that specializes in Internet-related services and products, which include online advertising technologies, search engine, cloud computing, software, and hardware. It is considered one of the Big Four technology companies, alongside Amazon, Apple, and Facebook. Google was founded in September 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University in California. Together they own about 14 percent of its shares and control 56 percent of the stockholder voting power through supervoting stock. They incorporated Google as a California privately held company on September 4, 1998, in California. Google was then reincorporated in Delaware on October 22, 2002. An initial public offering (IPO) took place on August 19, 2004, and Google moved to its headquarters in Mountain View, California, nicknamed the Googleplex. In August 2015, Google announced plans to reorganize its various interests as a conglomerate called Alphabet Inc. Google is Alphabet's leading subsidiary and will continue to be the umbrella company for Alphabet's Internet interests. Sundar Pichai was appointed CEO of Google, replacing Larry Page who became the CEO of Alphabet." const question = "Who is the CEO of Google?" const model = await qna.load(); const answers = await model.findAnswers(question, passage); console.log(answers); /** [{ text: "Sundar Pichai", startIndex: 1143, endIndex: 1156, score: 0.8380282521247864 }] **/"><pre><span class="pl-k">const</span> <span class="pl-s1">passage</span> <span class="pl-c1">=</span> <span class="pl-s">"Google LLC is an American multinational technology company that specializes in Internet-related services and products, which include online advertising technologies, search engine, cloud computing, software, and hardware. It is considered one of the Big Four technology companies, alongside Amazon, Apple, and Facebook. Google was founded in September 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University in California. Together they own about 14 percent of its shares and control 56 percent of the stockholder voting power through supervoting stock. They incorporated Google as a California privately held company on September 4, 1998, in California. Google was then reincorporated in Delaware on October 22, 2002. An initial public offering (IPO) took place on August 19, 2004, and Google moved to its headquarters in Mountain View, California, nicknamed the Googleplex. In August 2015, Google announced plans to reorganize its various interests as a conglomerate called Alphabet Inc. Google is Alphabet's leading subsidiary and will continue to be the umbrella company for Alphabet's Internet interests. Sundar Pichai was appointed CEO of Google, replacing Larry Page who became the CEO of Alphabet."</span> <span class="pl-k">const</span> <span class="pl-s1">question</span> <span class="pl-c1">=</span> <span class="pl-s">"Who is the CEO of Google?"</span> <span class="pl-k">const</span> <span class="pl-s1">model</span> <span class="pl-c1">=</span> <span class="pl-k">await</span> <span class="pl-s1">qna</span><span class="pl-kos">.</span><span class="pl-en">load</span><span class="pl-kos">(</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-k">const</span> <span class="pl-s1">answers</span> <span class="pl-c1">=</span> <span class="pl-k">await</span> <span class="pl-s1">model</span><span class="pl-kos">.</span><span class="pl-en">findAnswers</span><span class="pl-kos">(</span><span class="pl-s1">question</span><span class="pl-kos">,</span> <span class="pl-s1">passage</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-smi">console</span><span class="pl-kos">.</span><span class="pl-en">log</span><span class="pl-kos">(</span><span class="pl-s1">answers</span><span class="pl-kos">)</span><span class="pl-kos">;</span> <span class="pl-c">/**</span> <span class="pl-c">[{</span> <span class="pl-c"> text: "Sundar Pichai",</span> <span class="pl-c"> startIndex: 1143,</span> <span class="pl-c"> endIndex: 1156,</span> <span class="pl-c"> score: 0.8380282521247864</span> <span class="pl-c">}]</span> <span class="pl-c">**/</span></pre></div> </article></div></div></div></div></div></div></div><div class="Box-sc-g0xbh4-0"></div></div></div></div></div><div id="find-result-marks-container" class="Box-sc-g0xbh4-0 cCoXib"></div><button hidden="" data-testid="" data-hotkey-scope="read-only-cursor-text-area"></button><button hidden=""></button></div> <!-- --> <!-- --> <script type="application/json" id="__PRIMER_DATA_:R0:__">{"resolvedServerColorMode":"day"}</script></div> </react-app> </turbo-frame> </div> 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