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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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<script src="https://unpkg.com/[email protected]/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/[email protected]/+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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Image to text 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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<p class="mt-8"> |
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Pick the model you want to run. Check out over 100 models for image to text |
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<a |
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href="https://huggingface.co/tasks/image-to-text" |
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class="underline text-blue-500" |
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target="_blank" |
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> |
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here</a |
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>. The default model is for image captioning, but you can do text extraction, ... |
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</p> |
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<input |
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type="text" |
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id="model" |
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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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value="nlpconnect/vit-gpt2-image-captioning" |
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required |
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/> |
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<p class="mt-8">Finally the input image</p> |
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<input type="file" required accept="image/*" |
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class="rounded border-blue-500 shadow-md px-3 py-2 w-96 mt-6 block" |
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rows="5" |
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id="prompt" |
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/> |
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<button |
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id="submit" |
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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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> |
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Run |
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</button> |
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<p class="text-gray-400 text-sm">Output logs</p> |
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<div id="logs" class="bg-gray-100 rounded p-3 mb-8 text-sm"> |
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Output will be here |
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</div> |
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</form> |
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<script type="module"> |
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import { HfInference } from "@huggingface/inference"; |
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let running = false; |
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async function launch() { |
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if (running) { |
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return; |
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} |
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running = true; |
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try { |
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const hf = new HfInference( |
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document.getElementById("token").value.trim() || undefined |
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); |
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const model = document.getElementById("model").value.trim(); |
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const prompt = document.getElementById("prompt").files[0]; |
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document.getElementById("logs").textContent = ""; |
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const {generated_text} = await hf.imageToText({model, data: prompt}); |
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document.getElementById("logs").textContent = generated_text; |
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} catch (err) { |
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alert("Error: " + err.message); |
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} finally { |
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running = false; |
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} |
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} |
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window.launch = launch; |
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</script> |
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</body> |
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</html> |
