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	<!DOCTYPE html>
	<html lang="en">

	<head>
	<meta charset="UTF-8">
	<title>Zero Shot Classification - Hugging Face Transformers.js</title>

	<script type="module">
	// To-Do: transformers.js 라이브러리 중 pipeline 함수를 import하십시오.
	//import {pipleline} from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.4';
	import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.4';


	// Make it available globally
	window.pipeline = pipeline;
	</script>

	<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.0/dist/css/bootstrap.min.css" rel="stylesheet">

	<link rel="stylesheet" href="css/styles.css">
	</head>

	<body>
	<div class="container-main">

	<!-- Back to Home button -->
	<div class="row mt-5">
	<div class="col-md-12 text-center">
	<a href="index.html" class="btn btn-outline-secondary"
	style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a>
	</div>
	</div>

	<!-- Content -->
	<div class="container mt-5">
	<!-- Centered Titles -->
	<div class="text-center">
	<h2>Natural Language Processing</h2>
	<h4>Zero Shot Classification</h4>
	</div>

	<!-- Actual Content of this page -->
	<div id="zero-shot-classification-container" class="container mt-4">
	<h5>Zero Shot Classification with Xenova/mobilebert-uncased-mnli:</h5>
	<div class="d-flex align-items-center mb-2">
	<label for="textText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Text:</label>
	<input type="text" class="form-control flex-grow-1" id="textText" value="Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app."
	placeholder="Enter text" style="margin-right: 15px; margin-left: 15px;">
	</div>
	<div class="d-flex align-items-center">
	<label for="labelsText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Labels (comma separated):</label>
	<input type="text" class="form-control flex-grow-1" id="labelsText" value="mobile, billing, website, account access"
	placeholder="Enter labels (comma separated)" style="margin-right: 15px; margin-left: 15px;">
	<button id="classifyButton" class="btn btn-primary ml-2"
	onclick="classifyText()">Classify</button>
	</div>
	<div class="mt-4">
	<h4>Output:</h4>
	<pre id="outputArea"></pre>
	</div>
	</div>

	<hr> <!-- Line Separator -->

	<div id="zero-shot-classification-container-multi" class="container mt-4">
	<h5>Zero Shot Classification with Xenova/nli-deberta-v3-xsmall (Multi-Label):</h5>
	<div class="d-flex align-items-center mb-2">
	<label for="textTextMulti" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Text:</label>
	<input type="text" class="form-control flex-grow-1" id="textTextMulti" value="I have a problem with my iphone that needs to be resolved asap!"
	placeholder="Enter text" style="margin-right: 15px; margin-left: 15px;">
	</div>
	<div class="d-flex align-items-center">
	<label for="labelsTextMulti" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Labels (comma separated):</label>
	<input type="text" class="form-control flex-grow-1" id="labelsTextMulti" value="urgent, not urgent, phone, tablet, computer"
	placeholder="Enter labels (comma separated)" style="margin-right: 15px; margin-left: 15px;">
	<button id="classifyButtonMulti" class="btn btn-primary ml-2"
	onclick="classifyTextMulti()">Classify</button>
	</div>
	<div class="mt-4">
	<h4>Output:</h4>
	<pre id="outputAreaMulti"></pre>
	</div>
	</div>

	<!-- Back to Home button -->
	<div class="row mt-5">
	<div class="col-md-12 text-center">
	<a href="index.html" class="btn btn-outline-secondary"
	style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a>
	</div>
	</div>
	</div>
	</div>

	<script>

	let classifier;
	let classifierMulti;

	// Initialize the sentiment analysis model
	async function initializeModel() {
	// To-Do: pipeline 함수에 task와 model을 지정하여 zero 샷 분류 모델을 생성하여 classifier에 저장하십시오. 모델은 Xenova/mobilebert-uncased-mnli 사용
	//classifier = await pipeline('zero-shot-classification','Xenova/mobilebert-uncased-mnli')
	// To-Do: pipeline 함수에 task와 model을 지정하여 zero 샷 분류 모델을 생성하여 classifierMulti에 저장하십시오. 모델은 Xenova/nli-deberta-v3-xsmall 사용
	//classifierMulti = await pipeline('zero-shot-classification','Xenova/nli-deberta-v3-xsmall')

	classifier = await pipeline('zero-shot-classification', 'Xenova/mobilebert-uncased-mnli');
	classifierMulti = await pipeline('zero-shot-classification', 'Xenova/nli-deberta-v3-xsmall');

	}

	async function classifyText() {
	const text = document.getElementById("textText").value.trim();
	const labels = document.getElementById("labelsText").value.trim().split(",").map(item => item.trim());

	const result = await classifier(text, labels);

	document.getElementById("outputArea").innerText = JSON.stringify(result, null, 2);
	}

	async function classifyTextMulti() {
	const text = document.getElementById("textTextMulti").value.trim();
	const labels = document.getElementById("labelsTextMulti").value.trim().split(",").map(item => item.trim());

	const result = await classifierMulti(text, labels, { multi_label: true });

	document.getElementById("outputAreaMulti").innerText = JSON.stringify(result, null, 2);
	}

	// Initialize the model after the DOM is completely loaded
	window.addEventListener("DOMContentLoaded", initializeModel);
	</script>
	</body>

	</html>