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<title>Translation (Tokenizer & Model) - Hugging Face Transformers.js</title>
<script type="module">
// Import the library
import { AutoTokenizer, AutoModelForSeq2SeqLM } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.4';
// Make them available globally
window.AutoTokenizer = AutoTokenizer;
window.AutoModelForSeq2SeqLM = AutoModelForSeq2SeqLM;
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<div class="header">
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<img src="images/logo.png" alt="logo">
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<div class="header-main-text">
<h1>Hugging Face Transformers.js</h1>
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<div class="header-sub-text">
<h3>Free AI Models for JavaScript Web Development</h3>
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<h2>Natural Language Processing</h2>
<h4>Translation (Using Tokenizers and Models))</h4>
</div>
<!-- Actual Content of this page -->
<div id="translation-container" class="container mt-4">
<h5>Load and run an AutoModelForSeq2SeqLM Model and an AutoTokenizer:</h5>
<div class="d-flex align-items-center">
<label for="translationText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Text to
Translate:</label>
<input type="text" class="form-control flex-grow-1" id="translationText"
value="I love transformers!" placeholder="Enter text"
style="margin-right: 15px; margin-left: 15px;">
<button id="translateButton" class="btn btn-primary" onclick="translateText()">Translate</button>
</div>
<div class="mt-4">
<h4>Output:</h4>
<pre id="outputArea"></pre>
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<script>
let tokenizer;
let model;
// Initialize the sentiment analysis model
async function initializeModel() {
tokenizer = await AutoTokenizer.from_pretrained('Xenova/t5-small');
model = await AutoModelForSeq2SeqLM.from_pretrained('Xenova/t5-small');
}
async function translateText() {
const textFieldValue = document.getElementById("translationText").value.trim();
let { input_ids } = await tokenizer(textFieldValue);
console.log("input_ids: " + input_ids);
let outputs = await model.generate(input_ids);
let decoded = tokenizer.decode(outputs[0], { skip_special_tokens: true });
console.log("outputs: " + outputs);
console.log("decoded: " + decoded);
document.getElementById("outputArea").innerText = JSON.stringify(decoded, null, 2);
}
// Initialize the model after the DOM is completely loaded
window.addEventListener("DOMContentLoaded", initializeModel);
</script>
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