Create stream-textgeneration.html
Browse files- stream-textgeneration.html +130 -0
stream-textgeneration.html
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| 1 |
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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<script src="https://cdn.tailwindcss.com"></script>
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<!-- polyfill for firefox + import maps -->
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<script src="https://unpkg.com/es-module-shims@1.7.0/dist/es-module-shims.js"></script>
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<script type="importmap">
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{
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"imports": {
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"@huggingface/inference": "https://cdn.jsdelivr.net/npm/@huggingface/inference@1.7.1/+esm"
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}
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}
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</script>
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</head>
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<body>
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<form class="w-[90%] mx-auto pt-8" onsubmit="launch(); return false;">
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<h1 class="text-3xl font-bold">
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<span
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class="bg-clip-text text-transparent bg-gradient-to-r from-pink-500 to-violet-500"
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>
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Streaming text generation demo with
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<a href="https://github.com/huggingface/huggingface.js">
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<kbd>@huggingface/inference</kbd>
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</a>
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</span>
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</h1>
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<p class="mt-8">
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First, input your token if you have one! Otherwise, you may encounter
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rate limiting. You can create a token for free at
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<a
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target="_blank"
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href="https://huggingface.co/settings/tokens"
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class="underline text-blue-500"
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>hf.co/settings/tokens</a
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>
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</p>
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<input
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type="text"
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id="token"
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class="rounded border-2 border-blue-500 shadow-md px-3 py-2 w-96 mt-6"
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placeholder="token (optional)"
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/>
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| 47 |
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<p class="mt-8">
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Pick the model you want to run. Check out over 10k models for text to
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text generation
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| 51 |
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<a
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| 52 |
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href="https://huggingface.co/models?pipeline_tag=text2text-generation&sort=likes"
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| 53 |
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class="underline text-blue-500"
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| 54 |
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target="_blank"
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>
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here</a
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>
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</p>
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| 59 |
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<!-- Default model: https://huggingface.co/google/flan-t5-xxl -->
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<input
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type="text"
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id="model"
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| 64 |
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class="rounded border-2 border-blue-500 shadow-md px-3 py-2 w-96 mt-6"
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| 65 |
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value="google/flan-t5-xxl"
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| 66 |
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required
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| 67 |
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/>
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| 68 |
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| 69 |
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<p class="mt-8">Finally the prompt</p>
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| 70 |
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| 71 |
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<textarea
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| 72 |
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class="rounded border-blue-500 shadow-md px-3 py-2 w-96 mt-6 block"
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| 73 |
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rows="5"
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| 74 |
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id="prompt"
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| 75 |
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>
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| 76 |
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Q: How is butter made?
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| 77 |
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| 78 |
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Describe the process from the beginning
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| 79 |
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</textarea
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| 80 |
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>
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| 81 |
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| 82 |
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<button
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| 83 |
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id="submit"
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| 84 |
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class="my-8 bg-green-500 rounded py-3 px-5 text-white shadow-md disabled:bg-slate-300"
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| 85 |
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>
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| 86 |
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Run
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| 87 |
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</button>
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| 88 |
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| 89 |
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<p class="text-gray-400 text-sm">Output logs</p>
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| 90 |
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<div id="logs" class="bg-gray-100 rounded p-3 mb-8 text-sm">
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| 91 |
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Output will be here
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| 92 |
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</div>
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| 93 |
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| 94 |
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<p>Check out the <a class="underline text-blue-500" href="https://huggingface.co/spaces/huggingfacejs/streaming-text-generation/blob/main/index.html" target="_blank">source code</a></p>
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</form>
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| 96 |
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| 97 |
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<script type="module">
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| 98 |
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import { HfInference } from "@huggingface/inference";
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| 99 |
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let running = false;
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| 100 |
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async function launch() {
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| 101 |
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if (running) {
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| 102 |
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return;
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| 103 |
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}
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| 104 |
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running = true;
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| 105 |
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try {
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| 106 |
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const hf = new HfInference(
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| 107 |
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document.getElementById("token").value.trim() || undefined
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| 108 |
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);
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| 109 |
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const model = document.getElementById("model").value.trim();
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| 110 |
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const prompt = document.getElementById("prompt").value.trim();
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| 111 |
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document.getElementById("logs").textContent = "";
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| 112 |
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for await (const output of hf.textGenerationStream({
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| 113 |
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model,
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| 114 |
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inputs: prompt,
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| 115 |
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parameters: { max_new_tokens: 250 }
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| 116 |
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}, {
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| 117 |
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use_cache: false
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| 118 |
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})) {
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| 119 |
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document.getElementById("logs").textContent += output.token.text;
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| 120 |
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}
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| 121 |
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} catch (err) {
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| 122 |
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alert("Error: " + err.message);
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| 123 |
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} finally {
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| 124 |
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running = false;
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| 125 |
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}
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| 126 |
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}
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| 127 |
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window.launch = launch;
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| 128 |
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</script>
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| 129 |
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</body>
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| 130 |
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</html>
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