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| <title>NeuralForge - CPU LLM Training</title> | |
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| <h1 class="text-2xl font-bold">NeuralForge</h1> | |
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| <nav class="hidden md:flex space-x-6"> | |
| <a href="#" class="hover:text-blue-200">Dashboard</a> | |
| <a href="#" class="hover:text-blue-200">Models</a> | |
| <a href="#" class="hover:text-blue-200">Datasets</a> | |
| <a href="#" class="hover:text-blue-200">Training</a> | |
| <a href="#" class="hover:text-blue-200">Settings</a> | |
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| </header> | |
| <div class="mt-12 mb-16 text-center"> | |
| <h2 class="text-4xl font-bold mb-4">CPU-Powered LLM Training</h2> | |
| <p class="text-xl max-w-2xl mx-auto">Train language models efficiently using your CPU resources with our optimized training pipeline</p> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="container mx-auto px-4 py-8 -mt-10"> | |
| <div class="bg-white rounded-xl shadow-lg p-6 mb-8"> | |
| <div class="flex flex-col md:flex-row gap-6"> | |
| <div class="md:w-2/3"> | |
| <h3 class="text-xl font-semibold mb-4">Training Configuration</h3> | |
| <div class="grid grid-cols-1 md:grid-cols-2 gap-4 mb-6"> | |
| <div> | |
| <label class="block text-sm font-medium text-gray-700 mb-1">Model Architecture</label> | |
| <select class="w-full p-2 border border-gray-300 rounded-md focus:ring-2 focus:ring-blue-500 focus:border-blue-500"> | |
| <option>GPT-2 Small</option> | |
| <option>GPT-2 Medium</option> | |
| <option>BERT Base</option> | |
| <option>DistilBERT</option> | |
| <option>Custom...</option> | |
| </select> | |
| </div> | |
| <div> | |
| <label class="block text-sm font-medium text-gray-700 mb-1">Training Dataset</label> | |
| <select class="w-full p-2 border border-gray-300 rounded-md focus:ring-2 focus:ring-blue-500 focus:border-blue-500"> | |
| <option>Wikipedia (English)</option> | |
| <option>BookCorpus</option> | |
| <option>OpenWebText</option> | |
| <option>Custom Dataset</option> | |
| </select> | |
| </div> | |
| </div> | |
| <div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-6"> | |
| <div> | |
| <label class="block text-sm font-medium text-gray-700 mb-1">Batch Size</label> | |
| <input type="number" value="8" min="1" max="32" class="w-full p-2 border border-gray-300 rounded-md"> | |
| </div> | |
| <div> | |
| <label class="block text-sm font-medium text-gray-700 mb-1">Learning Rate</label> | |
| <input type="number" step="0.00001" value="0.0001" class="w-full p-2 border border-gray-300 rounded-md"> | |
| </div> | |
| <div> | |
| <label class="block text-sm font-medium text-gray-700 mb-1">Epochs</label> | |
| <input type="number" value="3" min="1" max="100" class="w-full p-2 border border-gray-300 rounded-md"> | |
| </div> | |
| </div> | |
| <div class="mb-6"> | |
| <label class="block text-sm font-medium text-gray-700 mb-2">CPU Threads (Max: <span id="maxThreads">8</span>)</label> | |
| <input type="range" min="1" max="8" value="4" class="w-full" id="threadSlider"> | |
| <div class="flex justify-between text-xs text-gray-500"> | |
| <span>1</span> | |
| <span>2</span> | |
| <span>3</span> | |
| <span>4</span> | |
| <span>5</span> | |
| <span>6</span> | |
| <span>7</span> | |
| <span>8</span> | |
| </div> | |
| </div> | |
| <div class="flex space-x-4"> | |
| <button id="startTraining" class="px-6 py-2 bg-blue-600 text-white rounded-md hover:bg-blue-700 transition flex items-center"> | |
| <i class="fas fa-play mr-2"></i> Start Training | |
| </button> | |
| <button class="px-6 py-2 border border-gray-300 rounded-md hover:bg-gray-50 transition flex items-center"> | |
| <i class="fas fa-save mr-2"></i> Save Config | |
| </button> | |
| <button id="stopTraining" class="px-6 py-2 border border-red-300 text-red-600 rounded-md hover:bg-red-50 transition flex items-center hidden"> | |
| <i class="fas fa-stop mr-2"></i> Stop Training | |
| </button> | |
| </div> | |
| </div> | |
| <div class="md:w-1/3 bg-gray-50 p-4 rounded-lg"> | |
| <h3 class="text-lg font-semibold mb-4">System Resources</h3> | |
| <div class="mb-4"> | |
| <div class="flex justify-between mb-1"> | |
| <span class="text-sm font-medium">CPU Utilization</span> | |
| <span id="cpuUsage" class="text-sm">0%</span> | |
| </div> | |
| <div class="w-full bg-gray-200 rounded-full h-2.5"> | |
| <div id="cpuBar" class="bg-blue-600 h-2.5 rounded-full" style="width: 0%"></div> | |
| </div> | |
| </div> | |
| <div class="mb-4"> | |
| <div class="flex justify-between mb-1"> | |
| <span class="text-sm font-medium">Memory Usage</span> | |
| <span id="memUsage" class="text-sm">0 GB / 16 GB</span> | |
| </div> | |
| <div class="w-full bg-gray-200 rounded-full h-2.5"> | |
| <div id="memBar" class="bg-green-600 h-2.5 rounded-full" style="width: 0%"></div> | |
| </div> | |
| </div> | |
| <div class="mb-4"> | |
| <div class="flex justify-between mb-1"> | |
| <span class="text-sm font-medium">Disk Cache</span> | |
| <span id="diskUsage" class="text-sm">0 GB / 50 GB</span> | |
| </div> | |
| <div class="w-full bg-gray-200 rounded-full h-2.5"> | |
| <div id="diskBar" class="bg-purple-600 h-2.5 rounded-full" style="width: 0%"></div> | |
| </div> | |
| </div> | |
| <div class="mt-6"> | |
| <h4 class="text-sm font-semibold mb-2">Estimated Training Time</h4> | |
| <div class="bg-white p-3 rounded-md border border-gray-200"> | |
| <div class="flex items-center"> | |
| <i class="fas fa-clock text-blue-500 mr-2"></i> | |
| <span id="estTime">Calculating...</span> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="grid grid-cols-1 md:grid-cols-2 gap-8 mb-8"> | |
| <div class="bg-white rounded-xl shadow-lg p-6"> | |
| <h3 class="text-xl font-semibold mb-4 flex items-center"> | |
| <i class="fas fa-terminal mr-2 text-blue-500"></i> Training Log | |
| </h3> | |
| <div id="terminal" class="terminal bg-black text-green-400 p-4 rounded-md font-mono text-sm overflow-y-auto"> | |
| <div>> Welcome to NeuralForge LLM Trainer</div> | |
| <div>> System ready for training configuration</div> | |
| <div>> CPU: 8 cores detected</div> | |
| <div>> RAM: 16GB available</div> | |
| </div> | |
| </div> | |
| <div class="bg-white rounded-xl shadow-lg p-6"> | |
| <h3 class="text-xl font-semibold mb-4 flex items-center"> | |
| <i class="fas fa-chart-line mr-2 text-blue-500"></i> Training Metrics | |
| </h3> | |
| <div class="grid grid-cols-2 gap-4 mb-4"> | |
| <div class="bg-gray-50 p-3 rounded-md"> | |
| <div class="text-sm text-gray-500">Loss</div> | |
| <div id="lossValue" class="text-2xl font-bold">--</div> | |
| </div> | |
| <div class="bg-gray-50 p-3 rounded-md"> | |
| <div class="text-sm text-gray-500">Perplexity</div> | |
| <div id="perplexityValue" class="text-2xl font-bold">--</div> | |
| </div> | |
| </div> | |
| <div class="h-48 bg-gray-50 rounded-md flex items-center justify-center"> | |
| <p class="text-gray-400">Training metrics will appear here</p> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="bg-white rounded-xl shadow-lg p-6 mb-8"> | |
| <h3 class="text-xl font-semibold mb-6">Available Model Architectures</h3> | |
| <div class="grid grid-cols-1 md:grid-cols-3 gap-6"> | |
| <div class="model-card bg-gray-50 p-5 rounded-lg border border-gray-200 transition duration-300 cursor-pointer hover:border-blue-300"> | |
| <div class="flex justify-between items-start mb-3"> | |
| <h4 class="font-semibold">GPT-2 Small</h4> | |
| <span class="bg-blue-100 text-blue-800 text-xs px-2 py-1 rounded">Recommended</span> | |
| </div> | |
| <p class="text-sm text-gray-600 mb-4">117M parameters, good for most tasks</p> | |
| <div class="text-xs text-gray-500"> | |
| <div class="flex justify-between mb-1"> | |
| <span>CPU RAM Needed:</span> | |
| <span>4GB</span> | |
| </div> | |
| <div class="flex justify-between"> | |
| <span>Training Time:</span> | |
| <span>~12 hours</span> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="model-card bg-gray-50 p-5 rounded-lg border border-gray-200 transition duration-300 cursor-pointer hover:border-blue-300"> | |
| <div class="flex justify-between items-start mb-3"> | |
| <h4 class="font-semibold">DistilBERT</h4> | |
| </div> | |
| <p class="text-sm text-gray-600 mb-4">66M parameters, distilled BERT model</p> | |
| <div class="text-xs text-gray-500"> | |
| <div class="flex justify-between mb-1"> | |
| <span>CPU RAM Needed:</span> | |
| <span>3GB</span> | |
| </div> | |
| <div class="flex justify-between"> | |
| <span>Training Time:</span> | |
| <span>~8 hours</span> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="model-card bg-gray-50 p-5 rounded-lg border border-gray-200 transition duration-300 cursor-pointer hover:border-blue-300"> | |
| <div class="flex justify-between items-start mb-3"> | |
| <h4 class="font-semibold">TinyLLAMA</h4> | |
| </div> | |
| <p class="text-sm text-gray-600 mb-4">28M parameters, lightweight option</p> | |
| <div class="text-xs text-gray-500"> | |
| <div class="flex justify-between mb-1"> | |
| <span>CPU RAM Needed:</span> | |
| <span>2GB</span> | |
| </div> | |
| <div class="flex justify-between"> | |
| <span>Training Time:</span> | |
| <span>~5 hours</span> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| <footer class="bg-gray-800 text-white py-8"> | |
| <div class="container mx-auto px-4"> | |
| <div class="flex flex-col md:flex-row justify-between"> | |
| <div class="mb-6 md:mb-0"> | |
| <h3 class="text-xl font-bold mb-4">NeuralForge</h3> | |
| <p class="text-gray-400 max-w-md">Optimized CPU training for language models. No GPU required.</p> | |
| </div> | |
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| <h4 class="text-sm font-semibold uppercase tracking-wider mb-4">Product</h4> | |
| <ul class="space-y-2"> | |
| <li><a href="#" class="text-gray-400 hover:text-white">Features</a></li> | |
| <li><a href="#" class="text-gray-400 hover:text-white">Pricing</a></li> | |
| <li><a href="#" class="text-gray-400 hover:text-white">Documentation</a></li> | |
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| <h4 class="text-sm font-semibold uppercase tracking-wider mb-4">Resources</h4> | |
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| <h4 class="text-sm font-semibold uppercase tracking-wider mb-4">Company</h4> | |
| <ul class="space-y-2"> | |
| <li><a href="#" class="text-gray-400 hover:text-white">About</a></li> | |
| <li><a href="#" class="text-gray-400 hover:text-white">Careers</a></li> | |
| <li><a href="#" class="text-gray-400 hover:text-white">Contact</a></li> | |
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| <div class="mt-8 pt-8 border-t border-gray-700 flex flex-col md:flex-row justify-between items-center"> | |
| <p class="text-gray-400 text-sm">© 2023 NeuralForge. All rights reserved.</p> | |
| <div class="flex space-x-6 mt-4 md:mt-0"> | |
| <a href="#" class="text-gray-400 hover:text-white"><i class="fab fa-twitter"></i></a> | |
| <a href="#" class="text-gray-400 hover:text-white"><i class="fab fa-github"></i></a> | |
| <a href="#" class="text-gray-400 hover:text-white"><i class="fab fa-linkedin"></i></a> | |
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| </footer> | |
| <script> | |
| // Simulate training process | |
| let trainingInterval; | |
| let isTraining = false; | |
| let epoch = 0; | |
| let totalEpochs = 3; | |
| let loss = 0; | |
| let perplexity = 0; | |
| document.getElementById('startTraining').addEventListener('click', startTraining); | |
| document.getElementById('stopTraining').addEventListener('click', stopTraining); | |
| document.getElementById('threadSlider').addEventListener('input', updateThreads); | |
| function updateThreads() { | |
| const threads = document.getElementById('threadSlider').value; | |
| document.getElementById('maxThreads').textContent = threads; | |
| updateEstTime(threads); | |
| } | |
| function updateEstTime(threads) { | |
| const baseTime = 12; // hours for GPT-2 Small with 4 threads | |
| const estTime = (baseTime * 4 / threads).toFixed(1); | |
| document.getElementById('estTime').textContent = `~${estTime} hours`; | |
| } | |
| function startTraining() { | |
| if (isTraining) return; | |
| isTraining = true; | |
| document.getElementById('startTraining').classList.add('hidden'); | |
| document.getElementById('stopTraining').classList.remove('hidden'); | |
| const terminal = document.getElementById('terminal'); | |
| terminal.innerHTML += '<div>> Starting training process...</div>'; | |
| terminal.scrollTop = terminal.scrollHeight; | |
| epoch = 0; | |
| loss = 4.5; | |
| perplexity = 120; | |
| // Update metrics | |
| document.getElementById('lossValue').textContent = loss.toFixed(4); | |
| document.getElementById('perplexityValue').textContent = Math.round(perplexity); | |
| // Simulate resource usage | |
| let cpuUsage = 10; | |
| let memUsage = 2; | |
| let diskUsage = 5; | |
| trainingInterval = setInterval(() => { | |
| // Simulate CPU usage | |
| cpuUsage = Math.min(100, cpuUsage + Math.random() * 10); | |
| document.getElementById('cpuUsage').textContent = Math.round(cpuUsage) + '%'; | |
| document.getElementById('cpuBar').style.width = cpuUsage + '%'; | |
| // Simulate memory usage | |
| memUsage = Math.min(16, memUsage + Math.random() * 0.5); | |
| document.getElementById('memUsage').textContent = memUsage.toFixed(1) + ' GB / 16 GB'; | |
| document.getElementById('memBar').style.width = (memUsage / 16 * 100) + '%'; | |
| // Simulate disk usage | |
| diskUsage = Math.min(50, diskUsage + Math.random() * 2); | |
| document.getElementById('diskUsage').textContent = diskUsage.toFixed(1) + ' GB / 50 GB'; | |
| document.getElementById('diskBar').style.width = (diskUsage / 50 * 100) + '%'; | |
| // Update training metrics | |
| if (Math.random() > 0.7) { | |
| loss = Math.max(0.5, loss - Math.random() * 0.3); | |
| perplexity = Math.max(10, perplexity - Math.random() * 5); | |
| document.getElementById('lossValue').textContent = loss.toFixed(4); | |
| document.getElementById('perplexityValue').textContent = Math.round(perplexity); | |
| // Add to terminal log | |
| if (Math.random() > 0.8) { | |
| epoch++; | |
| const progress = Math.min(100, Math.round((epoch / totalEpochs) * 100)); | |
| terminal.innerHTML += `<div>> Epoch ${epoch}/${totalEpochs} - Loss: ${loss.toFixed(4)} - Perplexity: ${Math.round(perplexity)}</div>`; | |
| terminal.scrollTop = terminal.scrollHeight; | |
| if (epoch >= totalEpochs) { | |
| stopTraining(); | |
| terminal.innerHTML += '<div class="text-green-300">> Training completed successfully!</div>'; | |
| terminal.scrollTop = terminal.scrollHeight; | |
| } | |
| } | |
| } | |
| }, 1000); | |
| } | |
| function stopTraining() { | |
| clearInterval(trainingInterval); | |
| isTraining = false; | |
| document.getElementById('startTraining').classList.remove('hidden'); | |
| document.getElementById('stopTraining').classList.add('hidden'); | |
| // Reset resource usage | |
| document.getElementById('cpuUsage').textContent = '0%'; | |
| document.getElementById('cpuBar').style.width = '0%'; | |
| document.getElementById('memUsage').textContent = '0 GB / 16 GB'; | |
| document.getElementById('memBar').style.width = '0%'; | |
| document.getElementById('diskUsage').textContent = '0 GB / 50 GB'; | |
| document.getElementById('diskBar').style.width = '0%'; | |
| } | |
| // Initialize | |
| updateThreads(); | |
| // Model card selection | |
| document.querySelectorAll('.model-card').forEach(card => { | |
| card.addEventListener('click', function() { | |
| document.querySelectorAll('.model-card').forEach(c => { | |
| c.classList.remove('border-blue-500', 'bg-blue-50'); | |
| }); | |
| this.classList.add('border-blue-500', 'bg-blue-50'); | |
| }); | |
| }); | |
| </script> | |
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