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Quarto GHA Workflow Runner
2026-04-02 12:08:47 +00:00
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@@ -176,6 +176,12 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
<a href="../docs/getting-started.html" class="sidebar-item-text sidebar-link active">
<span class="menu-text">Quickstart</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="../docs/choosing_method.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">Which Fine-Tuning Method Should I Use?</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
@@ -560,6 +566,24 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
<a href="../docs/rlhf.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">RLHF (Beta)</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="../docs/grpo.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">GRPO Training</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="../docs/ebft.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">EBFT Training</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="../docs/vllm_serving.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">vLLM Serving for GRPO Training</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
@@ -731,6 +755,12 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
<a href="../docs/faq.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">FAQ</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="../docs/training_stability.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">Training Stability &amp; Debugging</span></a>
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@@ -941,20 +971,28 @@ Tip
</section>
<section id="sec-next-steps" class="level2" data-number="5">
<h2 data-number="5" class="anchored" data-anchor-id="sec-next-steps"><span class="header-section-number">5</span> Next Steps</h2>
<p>Now that you have the basics, you might want to:</p>
<p>Now that you have the basics, explore these guides based on what you want to do:</p>
<p><strong>Choose your path:</strong></p>
<ul>
<li>Try different model architectures</li>
<li>Experiment with hyperparameters</li>
<li>Use more advanced training methods</li>
<li>Scale up to larger models</li>
<li><a href="../docs/choosing_method.html">Choosing a Fine-Tuning Method</a> — SFT vs LoRA vs QLoRA vs GRPO vs DPO, with hardware recommendations</li>
</ul>
<p>Check our other guides for details on these topics:</p>
<p><strong>Core guides:</strong></p>
<ul>
<li><a href="../docs/config-reference.html">Configuration Guide</a> - Full configuration options</li>
<li><a href="../docs/dataset_loading.html">Dataset Loading</a> - Loading datasets from various sources</li>
<li><a href="dataset-formats">Dataset Formats</a> - Working with different data formats</li>
<li><a href="../docs/multi-gpu.html">Multi-GPU Training</a></li>
<li><a href="../docs/multi-node.html">Multi-Node Training</a></li>
<li><a href="../docs/dataset_loading.html">Dataset Loading</a> — Loading datasets from various sources</li>
<li><a href="dataset-formats">Dataset Formats</a> — Working with different data formats</li>
<li><a href="../docs/optimizations.html">Optimizations</a> — Flash attention, gradient checkpointing, sample packing</li>
<li><a href="../docs/training_stability.html">Training Stability &amp; Debugging</a> — Monitoring metrics, fixing NaN, OOM debugging</li>
</ul>
<p><strong>Advanced training methods:</strong></p>
<ul>
<li><a href="../docs/rlhf.html">RLHF / Preference Learning</a> — DPO, KTO, GRPO, EBFT</li>
<li><a href="../docs/grpo.html">GRPO Training</a> — RL with custom rewards and vLLM generation</li>
<li><a href="../docs/vllm_serving.html">vLLM Serving</a> — Setting up vLLM for GRPO</li>
</ul>
<p><strong>Scaling up:</strong></p>
<ul>
<li><a href="../docs/multi-gpu.html">Multi-GPU Training</a> — DeepSpeed, FSDP, DDP</li>
<li><a href="../docs/multi-node.html">Multi-Node Training</a> — Distributed training across machines</li>
</ul>