File size: 5,907 Bytes
fea0eb7
 
 
 
 
 
 
 
736e977
 
fea0eb7
 
 
 
 
 
 
 
 
 
 
d0c56e2
fea0eb7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
736e977
 
fea0eb7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
<!DOCTYPE html>
<html lang="en">

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

    <script type="module">
        // Import the library
        import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/[email protected]';
        // Make it available globally
        window.pipeline = pipeline;
    </script>

    <link href="https://cdn.jsdelivr.net/npm/[email protected]/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() {
            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>