1107 lines
56 KiB
HTML
1107 lines
56 KiB
HTML
<!DOCTYPE html>
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<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
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<title>Axolotl</title>
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<link rel="stylesheet" href="styles.css">
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<body class="nav-sidebar docked nav-fixed quarto-light">
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<div id="quarto-search-results"></div>
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<nav class="navbar navbar-expand " data-bs-theme="dark">
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<div class="navbar-container container-fluid">
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<img src="./image/axolotl_logo_digital_white.svg" alt="" class="navbar-logo">
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<div id="quarto-search" class="" title="Search"></div>
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</div> <!-- /container-fluid -->
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</nav>
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<nav class="quarto-secondary-nav">
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<div class="container-fluid d-flex">
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<nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="./index.html">Home</a></li></ol></nav>
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</header>
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<!-- content -->
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<div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
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<a href="./index.html" class="sidebar-item-text sidebar-link active">
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<span class="menu-text">Home</span></a>
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<span class="menu-text">Getting Started</span></a>
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<span class="menu-text">Quickstart</span></a>
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<span class="menu-text">Installation</span></a>
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<span class="menu-text">Inference and Merging</span></a>
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<span class="menu-text">Command Line Interface (CLI)</span></a>
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<span class="menu-text">Config Reference</span></a>
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<span class="menu-text">API Reference</span></a>
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<span class="menu-text">Dataset Formats</span></a>
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<span class="menu-text">Instruction Tuning</span></a>
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<span class="menu-text">Stepwise Supervised Format</span></a>
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<span class="menu-text">Custom Pre-Tokenized Dataset</span></a>
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<li><a href="#latest-updates" id="toc-latest-updates" class="nav-link active" data-scroll-target="#latest-updates">🎉 Latest Updates</a></li>
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<li><a href="#quick-start---llm-fine-tuning-in-minutes" id="toc-quick-start---llm-fine-tuning-in-minutes" class="nav-link" data-scroll-target="#quick-start---llm-fine-tuning-in-minutes">🚀 Quick Start - LLM Fine-tuning in Minutes</a>
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<source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/887513285d98132142bf5db2a74eb5e0928787f1/image/axolotl_logo_digital_white.svg">
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<p align="center">
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<strong>A Free and Open Source LLM Fine-tuning Framework</strong><br>
|
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</p>
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<img src="https://img.shields.io/github/license/axolotl-ai-cloud/axolotl.svg?color=blue" alt="GitHub License">
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<a href="https://github.com/axolotl-ai-cloud/axolotl/releases"><img src="https://img.shields.io/github/release/axolotl-ai-cloud/axolotl.svg" alt="Releases"></a>
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<a href="https://colab.research.google.com/github/axolotl-ai-cloud/axolotl/blob/main/examples/colab-notebooks/colab-axolotl-example.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="google-colab" style="height: 20px;"></a>
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</p>
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<section id="latest-updates" class="level2">
|
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<h2 class="anchored" data-anchor-id="latest-updates">🎉 Latest Updates</h2>
|
||
<ul>
|
||
<li>2025/07:
|
||
<ul>
|
||
<li>ND Parallelism support has been added into Axolotl. Compose Context Parallelism (CP), Tensor Parallelism (TP), and Fully Sharded Data Parallelism (FSDP) within a single node and across multiple nodes. Check out the <a href="https://huggingface.co/blog/accelerate-nd-parallel">blog post</a> for more info.</li>
|
||
<li>Axolotl adds more models: <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/gpt-oss">GPT-OSS</a>, <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/gemma3n">Gemma 3n</a>, <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/lfm2">Liquid Foundation Model 2 (LFM2)</a>, and <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/afm">Arcee Foundation Models (AFM)</a>.</li>
|
||
<li>FP8 finetuning with fp8 gather op is now possible in Axolotl via <code>torchao</code>. Get started <a href="https://docs.axolotl.ai/docs/mixed_precision.html#sec-fp8">here</a>!</li>
|
||
<li><a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/voxtral">Voxtral</a>, <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/magistral">Magistral 1.1</a>, and <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/devstral">Devstral</a> with mistral-common tokenizer support has been integrated in Axolotl!</li>
|
||
<li>TiledMLP support for single-GPU to multi-GPU training with DDP, DeepSpeed and FSDP support has been added to support Arctic Long Sequence Training. (ALST). See <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/alst">examples</a> for using ALST with Axolotl!</li>
|
||
</ul></li>
|
||
<li>2025/05: Quantization Aware Training (QAT) support has been added to Axolotl. Explore the <a href="https://docs.axolotl.ai/docs/qat.html">docs</a> to learn more!</li>
|
||
<li>2025/03: Axolotl has implemented Sequence Parallelism (SP) support. Read the <a href="https://huggingface.co/blog/axolotl-ai-co/long-context-with-sequence-parallelism-in-axolotl">blog</a> and <a href="https://docs.axolotl.ai/docs/sequence_parallelism.html">docs</a> to learn how to scale your context length when fine-tuning.</li>
|
||
</ul>
|
||
<details>
|
||
<summary>
|
||
Expand older updates
|
||
</summary>
|
||
<ul>
|
||
<li>2025/06: Magistral with mistral-common tokenizer support has been added to Axolotl. See <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/magistral">examples</a> to start training your own Magistral models with Axolotl!</li>
|
||
<li>2025/04: Llama 4 support has been added in Axolotl. See <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/llama-4">examples</a> to start training your own Llama 4 models with Axolotl’s linearized version!</li>
|
||
<li>2025/03: (Beta) Fine-tuning Multimodal models is now supported in Axolotl. Check out the <a href="https://docs.axolotl.ai/docs/multimodal.html">docs</a> to fine-tune your own!</li>
|
||
<li>2025/02: Axolotl has added LoRA optimizations to reduce memory usage and improve training speed for LoRA and QLoRA in single GPU and multi-GPU training (DDP and DeepSpeed). Jump into the <a href="https://docs.axolotl.ai/docs/lora_optims.html">docs</a> to give it a try.</li>
|
||
<li>2025/02: Axolotl has added GRPO support. Dive into our <a href="https://huggingface.co/blog/axolotl-ai-co/training-llms-w-interpreter-feedback-wasm">blog</a> and <a href="https://github.com/axolotl-ai-cloud/grpo_code">GRPO example</a> and have some fun!</li>
|
||
<li>2025/01: Axolotl has added Reward Modelling / Process Reward Modelling fine-tuning support. See <a href="https://docs.axolotl.ai/docs/reward_modelling.html">docs</a>.</li>
|
||
</ul>
|
||
</details>
|
||
</section>
|
||
<section id="overview" class="level2">
|
||
<h2 class="anchored" data-anchor-id="overview">✨ Overview</h2>
|
||
<p>Axolotl is a free and open-source tool designed to streamline post-training and fine-tuning for the latest large language models (LLMs).</p>
|
||
<p>Features:</p>
|
||
<ul>
|
||
<li><strong>Multiple Model Support</strong>: Train various models like GPT-OSS, LLaMA, Mistral, Mixtral, Pythia, and many more models available on the Hugging Face Hub.</li>
|
||
<li><strong>Multimodal Training</strong>: Fine-tune vision-language models (VLMs) including LLaMA-Vision, Qwen2-VL, Pixtral, LLaVA, SmolVLM2, and audio models like Voxtral with image, video, and audio support.</li>
|
||
<li><strong>Training Methods</strong>: Full fine-tuning, LoRA, QLoRA, GPTQ, QAT, Preference Tuning (DPO, IPO, KTO, ORPO), RL (GRPO), and Reward Modelling (RM) / Process Reward Modelling (PRM).</li>
|
||
<li><strong>Easy Configuration</strong>: Re-use a single YAML configuration file across the full fine-tuning pipeline: dataset preprocessing, training, evaluation, quantization, and inference.</li>
|
||
<li><strong>Performance Optimizations</strong>: <a href="https://docs.axolotl.ai/docs/multipack.html">Multipacking</a>, <a href="https://github.com/Dao-AILab/flash-attention">Flash Attention</a>, <a href="https://github.com/facebookresearch/xformers">Xformers</a>, <a href="https://pytorch.org/blog/flexattention/">Flex Attention</a>, <a href="https://github.com/linkedin/Liger-Kernel">Liger Kernel</a>, <a href="https://github.com/apple/ml-cross-entropy/tree/main">Cut Cross Entropy</a>, <a href="https://docs.axolotl.ai/docs/sequence_parallelism.html">Sequence Parallelism (SP)</a>, <a href="https://docs.axolotl.ai/docs/lora_optims.html">LoRA optimizations</a>, <a href="https://docs.axolotl.ai/docs/multi-gpu.html">Multi-GPU training (FSDP1, FSDP2, DeepSpeed)</a>, <a href="https://docs.axolotl.ai/docs/multi-node.html">Multi-node training (Torchrun, Ray)</a>, and many more!</li>
|
||
<li><strong>Flexible Dataset Handling</strong>: Load from local, HuggingFace, and cloud (S3, Azure, GCP, OCI) datasets.</li>
|
||
<li><strong>Cloud Ready</strong>: We ship <a href="https://hub.docker.com/u/axolotlai">Docker images</a> and also <a href="https://pypi.org/project/axolotl/">PyPI packages</a> for use on cloud platforms and local hardware.</li>
|
||
</ul>
|
||
</section>
|
||
<section id="quick-start---llm-fine-tuning-in-minutes" class="level2">
|
||
<h2 class="anchored" data-anchor-id="quick-start---llm-fine-tuning-in-minutes">🚀 Quick Start - LLM Fine-tuning in Minutes</h2>
|
||
<p><strong>Requirements</strong>:</p>
|
||
<ul>
|
||
<li>NVIDIA GPU (Ampere or newer for <code>bf16</code> and Flash Attention) or AMD GPU</li>
|
||
<li>Python 3.11</li>
|
||
<li>PyTorch ≥2.6.0</li>
|
||
</ul>
|
||
<section id="google-colab" class="level3">
|
||
<h3 class="anchored" data-anchor-id="google-colab">Google Colab</h3>
|
||
<div class="quarto-figure quarto-figure-center">
|
||
<figure class="figure">
|
||
<p><a href="https://colab.research.google.com/github/axolotl-ai-cloud/axolotl/blob/main/examples/colab-notebooks/colab-axolotl-example.ipynb#scrollTo=msOCO4NRmRLa"><img src="https://colab.research.google.com/assets/colab-badge.svg" class="img-fluid figure-img"></a></p>
|
||
<figcaption>Open In Colab</figcaption>
|
||
</figure>
|
||
</div>
|
||
</section>
|
||
<section id="installation" class="level3">
|
||
<h3 class="anchored" data-anchor-id="installation">Installation</h3>
|
||
<section id="using-pip" class="level4">
|
||
<h4 class="anchored" data-anchor-id="using-pip">Using pip</h4>
|
||
<div class="sourceCode" id="cb1"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> install <span class="at">-U</span> packaging==23.2 setuptools==75.8.0 wheel ninja</span>
|
||
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> install <span class="at">--no-build-isolation</span> axolotl<span class="pp">[</span><span class="ss">flash</span><span class="pp">-</span><span class="ss">attn,deepspeed</span><span class="pp">]</span></span>
|
||
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a></span>
|
||
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="co"># Download example axolotl configs, deepspeed configs</span></span>
|
||
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="ex">axolotl</span> fetch examples</span>
|
||
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="ex">axolotl</span> fetch deepspeed_configs <span class="co"># OPTIONAL</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||
</section>
|
||
<section id="using-docker" class="level4">
|
||
<h4 class="anchored" data-anchor-id="using-docker">Using Docker</h4>
|
||
<p>Installing with Docker can be less error prone than installing in your own environment.</p>
|
||
<div class="sourceCode" id="cb2"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="ex">docker</span> run <span class="at">--gpus</span> <span class="st">'"all"'</span> <span class="at">--rm</span> <span class="at">-it</span> axolotlai/axolotl:main-latest</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||
<p>Other installation approaches are described <a href="https://docs.axolotl.ai/docs/installation.html">here</a>.</p>
|
||
</section>
|
||
<section id="cloud-providers" class="level4">
|
||
<h4 class="anchored" data-anchor-id="cloud-providers">Cloud Providers</h4>
|
||
<details>
|
||
<ul>
|
||
<li><a href="https://runpod.io/gsc?template=v2ickqhz9s&ref=6i7fkpdz">RunPod</a></li>
|
||
<li><a href="https://cloud.vast.ai?ref_id=62897&template_id=bdd4a49fa8bce926defc99471864cace&utm_source=github&utm_medium=developer_community&utm_campaign=template_launch_axolotl&utm_content=readme">Vast.ai</a></li>
|
||
<li><a href="https://app.primeintellect.ai/dashboard/create-cluster?image=axolotl&location=Cheapest&security=Cheapest&show_spot=true">PRIME Intellect</a></li>
|
||
<li><a href="https://www.modal.com?utm_source=github&utm_medium=github&utm_campaign=axolotl">Modal</a></li>
|
||
<li><a href="https://novita.ai/gpus-console?templateId=311">Novita</a></li>
|
||
<li><a href="https://jarvislabs.ai/templates/axolotl">JarvisLabs.ai</a></li>
|
||
<li><a href="https://latitude.sh/blueprint/989e0e79-3bf6-41ea-a46b-1f246e309d5c">Latitude.sh</a></li>
|
||
</ul>
|
||
</details>
|
||
</section>
|
||
</section>
|
||
<section id="your-first-fine-tune" class="level3">
|
||
<h3 class="anchored" data-anchor-id="your-first-fine-tune">Your First Fine-tune</h3>
|
||
<div class="sourceCode" id="cb3"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Fetch axolotl examples</span></span>
|
||
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="ex">axolotl</span> fetch examples</span>
|
||
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a></span>
|
||
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a><span class="co"># Or, specify a custom path</span></span>
|
||
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a><span class="ex">axolotl</span> fetch examples <span class="at">--dest</span> path/to/folder</span>
|
||
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a></span>
|
||
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a><span class="co"># Train a model using LoRA</span></span>
|
||
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a><span class="ex">axolotl</span> train examples/llama-3/lora-1b.yml</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||
<p>That’s it! Check out our <a href="https://docs.axolotl.ai/docs/getting-started.html">Getting Started Guide</a> for a more detailed walkthrough.</p>
|
||
</section>
|
||
</section>
|
||
<section id="documentation" class="level2">
|
||
<h2 class="anchored" data-anchor-id="documentation">📚 Documentation</h2>
|
||
<ul>
|
||
<li><a href="https://docs.axolotl.ai/docs/installation.html">Installation Options</a> - Detailed setup instructions for different environments</li>
|
||
<li><a href="https://docs.axolotl.ai/docs/config-reference.html">Configuration Guide</a> - Full configuration options and examples</li>
|
||
<li><a href="https://docs.axolotl.ai/docs/dataset_loading.html">Dataset Loading</a> - Loading datasets from various sources</li>
|
||
<li><a href="https://docs.axolotl.ai/docs/dataset-formats/">Dataset Guide</a> - Supported formats and how to use them</li>
|
||
<li><a href="https://docs.axolotl.ai/docs/multi-gpu.html">Multi-GPU Training</a></li>
|
||
<li><a href="https://docs.axolotl.ai/docs/multi-node.html">Multi-Node Training</a></li>
|
||
<li><a href="https://docs.axolotl.ai/docs/multipack.html">Multipacking</a></li>
|
||
<li><a href="https://docs.axolotl.ai/docs/api/">API Reference</a> - Auto-generated code documentation</li>
|
||
<li><a href="https://docs.axolotl.ai/docs/faq.html">FAQ</a> - Frequently asked questions</li>
|
||
</ul>
|
||
</section>
|
||
<section id="getting-help" class="level2">
|
||
<h2 class="anchored" data-anchor-id="getting-help">🤝 Getting Help</h2>
|
||
<ul>
|
||
<li>Join our <a href="https://discord.gg/HhrNrHJPRb">Discord community</a> for support</li>
|
||
<li>Check out our <a href="https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/">Examples</a> directory</li>
|
||
<li>Read our <a href="https://docs.axolotl.ai/docs/debugging.html">Debugging Guide</a></li>
|
||
<li>Need dedicated support? Please contact <a href="mailto:wing@axolotl.ai">✉️wing@axolotl.ai</a> for options</li>
|
||
</ul>
|
||
</section>
|
||
<section id="contributing" class="level2">
|
||
<h2 class="anchored" data-anchor-id="contributing">🌟 Contributing</h2>
|
||
<p>Contributions are welcome! Please see our <a href="https://github.com/axolotl-ai-cloud/axolotl/blob/main/.github/CONTRIBUTING.md">Contributing Guide</a> for details.</p>
|
||
</section>
|
||
<section id="sponsors" class="level2">
|
||
<h2 class="anchored" data-anchor-id="sponsors">❤️ Sponsors</h2>
|
||
<p>Interested in sponsoring? Contact us at <a href="mailto:wing@axolotl.ai">wing@axolotl.ai</a></p>
|
||
</section>
|
||
<section id="citing-axolotl" class="level2">
|
||
<h2 class="anchored" data-anchor-id="citing-axolotl">📝 Citing Axolotl</h2>
|
||
<p>If you use Axolotl in your research or projects, please cite it as follows:</p>
|
||
<div class="sourceCode" id="cb4"><pre class="sourceCode bibtex code-with-copy"><code class="sourceCode bibtex"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co">@software{axolotl,</span></span>
|
||
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="co"> title = {Axolotl: Open Source LLM Post-Training},</span></span>
|
||
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a><span class="co"> author = {{Axolotl maintainers and contributors}},</span></span>
|
||
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a><span class="co"> url = {https://github.com/axolotl-ai-cloud/axolotl},</span></span>
|
||
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a><span class="co"> license = {Apache-2.0},</span></span>
|
||
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a><span class="co"> year = {2023}</span></span>
|
||
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a><span class="co">}</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||
</section>
|
||
<section id="license" class="level2">
|
||
<h2 class="anchored" data-anchor-id="license">📜 License</h2>
|
||
<p>This project is licensed under the Apache 2.0 License - see the <a href="LICENSE">LICENSE</a> file for details.</p>
|
||
|
||
|
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</section>
|
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|
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||
// Handle positioning of the toggle
|
||
window.addEventListener(
|
||
"resize",
|
||
throttle(() => {
|
||
elRect = undefined;
|
||
if (selectedAnnoteEl) {
|
||
selectCodeLines(selectedAnnoteEl);
|
||
}
|
||
}, 10)
|
||
);
|
||
function throttle(fn, ms) {
|
||
let throttle = false;
|
||
let timer;
|
||
return (...args) => {
|
||
if(!throttle) { // first call gets through
|
||
fn.apply(this, args);
|
||
throttle = true;
|
||
} else { // all the others get throttled
|
||
if(timer) clearTimeout(timer); // cancel #2
|
||
timer = setTimeout(() => {
|
||
fn.apply(this, args);
|
||
timer = throttle = false;
|
||
}, ms);
|
||
}
|
||
};
|
||
}
|
||
// Attach click handler to the DT
|
||
const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');
|
||
for (const annoteDlNode of annoteDls) {
|
||
annoteDlNode.addEventListener('click', (event) => {
|
||
const clickedEl = event.target;
|
||
if (clickedEl !== selectedAnnoteEl) {
|
||
unselectCodeLines();
|
||
const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active');
|
||
if (activeEl) {
|
||
activeEl.classList.remove('code-annotation-active');
|
||
}
|
||
selectCodeLines(clickedEl);
|
||
clickedEl.classList.add('code-annotation-active');
|
||
} else {
|
||
// Unselect the line
|
||
unselectCodeLines();
|
||
clickedEl.classList.remove('code-annotation-active');
|
||
}
|
||
});
|
||
}
|
||
const findCites = (el) => {
|
||
const parentEl = el.parentElement;
|
||
if (parentEl) {
|
||
const cites = parentEl.dataset.cites;
|
||
if (cites) {
|
||
return {
|
||
el,
|
||
cites: cites.split(' ')
|
||
};
|
||
} else {
|
||
return findCites(el.parentElement)
|
||
}
|
||
} else {
|
||
return undefined;
|
||
}
|
||
};
|
||
var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
|
||
for (var i=0; i<bibliorefs.length; i++) {
|
||
const ref = bibliorefs[i];
|
||
const citeInfo = findCites(ref);
|
||
if (citeInfo) {
|
||
tippyHover(citeInfo.el, function() {
|
||
var popup = window.document.createElement('div');
|
||
citeInfo.cites.forEach(function(cite) {
|
||
var citeDiv = window.document.createElement('div');
|
||
citeDiv.classList.add('hanging-indent');
|
||
citeDiv.classList.add('csl-entry');
|
||
var biblioDiv = window.document.getElementById('ref-' + cite);
|
||
if (biblioDiv) {
|
||
citeDiv.innerHTML = biblioDiv.innerHTML;
|
||
}
|
||
popup.appendChild(citeDiv);
|
||
});
|
||
return popup.innerHTML;
|
||
});
|
||
}
|
||
}
|
||
});
|
||
</script>
|
||
</div> <!-- /content -->
|
||
|
||
|
||
|
||
|
||
</body></html> |