Jong Wook Kim
detector model
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<!doctype html>
<html>
<head>
<title>GPT-2 Output Detector</title>
<style type="text/css">
* {
box-sizing: border-box;
}
body {
font-family: sans-serif;
margin: 0;
}
h1 {
font-weight: lighter;
}
a {
text-decoration: none;
color: #666;
}
a:hover {
text-decoration: underline;
}
#container {
margin: auto;
width: 960px;
}
#textbox {
font-family: serif;
font-size: 16pt;
width: 100%;
height: 480px;
padding: 20px 30px;
line-height: 1.6;
}
.bar-row {
height: 30px;
}
#real-percentage {
width: 80px;
vertical-align: top;
}
#bar-container {
width: 800px;
background-color: #ff7674;
line-height: 0.5;
position:relative;
top:6px;
}
#fake-percentage {
width: 80px;
vertical-align: top;
}
#bar {
display: inline-block;
height: 30px;
background-color: #83aaff;
}
em {
font-family: monospace;
font-style: normal;
}
</style>
</head>
<body>
<div id="container">
<h1>GPT-2 Output Detector Demo</h1>
<p>
This is an online demo of the
<a href="https://github.com/openai/gpt-2-output-dataset/tree/master/detector">GPT-2 output detector</a>
model. Enter some text in the text box; the predicted probabilities will be displayed below.
<u>The results start to get reliable after around 50 tokens.</u>
</p>
<textarea id="textbox" placeholder="Enter text here"></textarea>
<div><table cellspacing="0" cellpadding="0">
<tr class="bar-row" style="vertical-align: bottom;">
<td style="text-align: left;">Real</td>
<td id="message" style="text-align: center;"></td>
<td style="text-align: right;">Fake</td>
</tr>
<tr class="bar-row">
<td id="real-percentage" style="text-align: left; vertical-align: bottom;"></td>
<td id="bar-container"><div id="bar" style="width: 50%;"></div></td>
<td id="fake-percentage" style="text-align: right; vertical-align: bottom;"></td>
</tr>
</table></div>
</div>
<script>
let textbox = document.getElementById('textbox');
let last_submit = null;
let real_percentage = document.getElementById('real-percentage');
let fake_percentage = document.getElementById('fake-percentage');
let bar = document.getElementById('bar');
let message = document.getElementById('message');
function update_graph(result) {
if (result === null) {
real_percentage.innerHTML = '';
fake_percentage.innerHTML = '';
bar.style.width = '50%';
message.innerHTML = '';
} else {
let percentage = result.real_probability;
real_percentage.innerHTML = (100 * percentage).toFixed(2) + '%';
fake_percentage.innerHTML = (100 * (1 - percentage)).toFixed(2) + '%';
bar.style.width = (100 * percentage).toFixed(2) + '%';
if (result.used_tokens === result.all_tokens) {
message.innerHTML = `Prediction based on ${result.used_tokens} tokens`;
} else {
message.innerHTML = `Prediction based on the first ${result.used_tokens} tokens among the total ${result.all_tokens}`;
}
}
}
textbox.oninput = () => {
if (last_submit) {
clearTimeout(last_submit);
}
if (textbox.value.length === 0) {
update_graph(null);
return;
}
message.innerText = 'Predicting ...';
last_submit = setTimeout(() => {
let req = new XMLHttpRequest();
if (textbox.value.length === 0) {
update_graph(null);
return;
}
req.open('GET', '/?' + textbox.value, true);
req.onreadystatechange = () => {
if (req.readyState !== 4) return;
if (req.status !== 200) throw new Error("HTTP status: " + req.status);
let result = JSON.parse(req.responseText);
update_graph(result);
};
req.send();
}, 1000);
};
window.addEventListener('DOMContentLoaded', () => {
textbox.focus();
});
</script>
</body>
</html>