From 866a618cb40bd5e6daacf09ad5f32ceb561bb12f Mon Sep 17 00:00:00 2001
From: Quarto GHA Workflow Runner <quarto-github-actions-publish@example.com>
Date: Sat, 16 Aug 2025 01:30:52 +0000
Subject: [PATCH] Built site for gh-pages

---
 .nojekyll           |   2 +-
 docs/api/train.html | 167 ++++++-------------
 search.json         |   4 +-
 sitemap.xml         | 394 ++++++++++++++++++++++----------------------
 4 files changed, 253 insertions(+), 314 deletions(-)

diff --git a/.nojekyll b/.nojekyll
index 9e9b791a0..4c966a6a0 100644
--- a/.nojekyll
+++ b/.nojekyll
@@ -1 +1 @@
-522f6e63
\ No newline at end of file
+4627db41
\ No newline at end of file
diff --git a/docs/api/train.html b/docs/api/train.html
index 837ad0d49..7696176d9 100644
--- a/docs/api/train.html
+++ b/docs/api/train.html
@@ -496,7 +496,6 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
   <li><a href="#functions" id="toc-functions" class="nav-link" data-scroll-target="#functions">Functions</a>
   <ul class="collapse">
   <li><a href="#axolotl.train.create_model_card" id="toc-axolotl.train.create_model_card" class="nav-link" data-scroll-target="#axolotl.train.create_model_card">create_model_card</a></li>
-  <li><a href="#axolotl.train.determine_resume_checkpoint" id="toc-axolotl.train.determine_resume_checkpoint" class="nav-link" data-scroll-target="#axolotl.train.determine_resume_checkpoint">determine_resume_checkpoint</a></li>
   <li><a href="#axolotl.train.execute_training" id="toc-axolotl.train.execute_training" class="nav-link" data-scroll-target="#axolotl.train.execute_training">execute_training</a></li>
   <li><a href="#axolotl.train.handle_untrained_tokens_fix" id="toc-axolotl.train.handle_untrained_tokens_fix" class="nav-link" data-scroll-target="#axolotl.train.handle_untrained_tokens_fix">handle_untrained_tokens_fix</a></li>
   <li><a href="#axolotl.train.save_initial_configs" id="toc-axolotl.train.save_initial_configs" class="nav-link" data-scroll-target="#axolotl.train.save_initial_configs">save_initial_configs</a></li>
@@ -537,46 +536,42 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
 <td>Create a model card for the trained model if needed.</td>
 </tr>
 <tr class="even">
-<td><a href="#axolotl.train.determine_resume_checkpoint">determine_resume_checkpoint</a></td>
-<td>Determine the checkpoint to resume from based on configuration.</td>
-</tr>
-<tr class="odd">
 <td><a href="#axolotl.train.execute_training">execute_training</a></td>
 <td>Execute the training process with appropriate SDP kernel configurations.</td>
 </tr>
-<tr class="even">
+<tr class="odd">
 <td><a href="#axolotl.train.handle_untrained_tokens_fix">handle_untrained_tokens_fix</a></td>
 <td>Apply fixes for untrained tokens if configured.</td>
 </tr>
-<tr class="odd">
+<tr class="even">
 <td><a href="#axolotl.train.save_initial_configs">save_initial_configs</a></td>
 <td>Save initial configurations before training.</td>
 </tr>
-<tr class="even">
+<tr class="odd">
 <td><a href="#axolotl.train.save_trained_model">save_trained_model</a></td>
 <td>Save the trained model according to configuration and training setup.</td>
 </tr>
-<tr class="odd">
+<tr class="even">
 <td><a href="#axolotl.train.setup_model_and_tokenizer">setup_model_and_tokenizer</a></td>
 <td>Load the tokenizer, processor (for multimodal models), and model based on</td>
 </tr>
-<tr class="even">
+<tr class="odd">
 <td><a href="#axolotl.train.setup_model_and_trainer">setup_model_and_trainer</a></td>
 <td>Load model, tokenizer, trainer, etc. Helper function to encapsulate the full</td>
 </tr>
-<tr class="odd">
+<tr class="even">
 <td><a href="#axolotl.train.setup_model_card">setup_model_card</a></td>
 <td>Set up the Axolotl badge and add the Axolotl config to the model card if available.</td>
 </tr>
-<tr class="even">
+<tr class="odd">
 <td><a href="#axolotl.train.setup_reference_model">setup_reference_model</a></td>
 <td>Set up the reference model for RL training if needed.</td>
 </tr>
-<tr class="odd">
+<tr class="even">
 <td><a href="#axolotl.train.setup_signal_handler">setup_signal_handler</a></td>
 <td>Set up signal handler for graceful termination.</td>
 </tr>
-<tr class="even">
+<tr class="odd">
 <td><a href="#axolotl.train.train">train</a></td>
 <td>Train a model on the given dataset.</td>
 </tr>
@@ -620,68 +615,12 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
 </table>
 </section>
 </section>
-<section id="axolotl.train.determine_resume_checkpoint" class="level3">
-<h3 class="anchored" data-anchor-id="axolotl.train.determine_resume_checkpoint">determine_resume_checkpoint</h3>
-<div class="sourceCode" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>train.determine_resume_checkpoint(cfg)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>Determine the checkpoint to resume from based on configuration.</p>
-<section id="parameters-1" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-1">Parameters</h4>
-<table class="caption-top table">
-<colgroup>
-<col style="width: 9%">
-<col style="width: 15%">
-<col style="width: 61%">
-<col style="width: 13%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Name</th>
-<th>Type</th>
-<th>Description</th>
-<th>Default</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td>cfg</td>
-<td>DictDefault</td>
-<td>Dictionary mapping <code>axolotl</code> config keys to values.</td>
-<td><em>required</em></td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="returns" class="level4 doc-section doc-section-returns">
-<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns">Returns</h4>
-<table class="caption-top table">
-<colgroup>
-<col style="width: 9%">
-<col style="width: 14%">
-<col style="width: 76%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Name</th>
-<th>Type</th>
-<th>Description</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td></td>
-<td>str | None</td>
-<td>Path to the checkpoint to resume from, or <code>None</code> if not resuming.</td>
-</tr>
-</tbody>
-</table>
-</section>
-</section>
 <section id="axolotl.train.execute_training" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.execute_training">execute_training</h3>
-<div class="sourceCode" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>train.execute_training(cfg, trainer, resume_from_checkpoint)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>train.execute_training(cfg, trainer, resume_from_checkpoint)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Execute the training process with appropriate SDP kernel configurations.</p>
-<section id="parameters-2" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-2">Parameters</h4>
+<section id="parameters-1" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-1">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 23%">
@@ -722,16 +661,16 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
 </section>
 <section id="axolotl.train.handle_untrained_tokens_fix" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.handle_untrained_tokens_fix">handle_untrained_tokens_fix</h3>
-<div class="sourceCode" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>train.handle_untrained_tokens_fix(</span>
-<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a>    cfg,</span>
-<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a>    model,</span>
-<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a>    tokenizer,</span>
-<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a>    train_dataset,</span>
-<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a>    safe_serialization,</span>
-<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>train.handle_untrained_tokens_fix(</span>
+<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>    cfg,</span>
+<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a>    model,</span>
+<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a>    tokenizer,</span>
+<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a>    train_dataset,</span>
+<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a>    safe_serialization,</span>
+<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Apply fixes for untrained tokens if configured.</p>
-<section id="parameters-3" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-3">Parameters</h4>
+<section id="parameters-2" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-2">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 18%">
@@ -784,10 +723,10 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
 </section>
 <section id="axolotl.train.save_initial_configs" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.save_initial_configs">save_initial_configs</h3>
-<div class="sourceCode" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>train.save_initial_configs(cfg, tokenizer, model, peft_config, processor)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>train.save_initial_configs(cfg, tokenizer, model, peft_config, processor)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Save initial configurations before training.</p>
-<section id="parameters-4" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-4">Parameters</h4>
+<section id="parameters-3" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-3">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 13%">
@@ -834,10 +773,10 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
 </section>
 <section id="axolotl.train.save_trained_model" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.save_trained_model">save_trained_model</h3>
-<div class="sourceCode" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>train.save_trained_model(cfg, trainer, model, safe_serialization)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>train.save_trained_model(cfg, trainer, model, safe_serialization)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Save the trained model according to configuration and training setup.</p>
-<section id="parameters-5" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-5">Parameters</h4>
+<section id="parameters-4" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-4">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 19%">
@@ -884,11 +823,11 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
 </section>
 <section id="axolotl.train.setup_model_and_tokenizer" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.setup_model_and_tokenizer">setup_model_and_tokenizer</h3>
-<div class="sourceCode" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>train.setup_model_and_tokenizer(cfg)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>train.setup_model_and_tokenizer(cfg)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Load the tokenizer, processor (for multimodal models), and model based on
 configuration.</p>
-<section id="parameters-6" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-6">Parameters</h4>
+<section id="parameters-5" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-5">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 9%">
@@ -914,8 +853,8 @@ configuration.</p>
 </tbody>
 </table>
 </section>
-<section id="returns-1" class="level4 doc-section doc-section-returns">
-<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns-1">Returns</h4>
+<section id="returns" class="level4 doc-section doc-section-returns">
+<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns">Returns</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 3%">
@@ -941,11 +880,11 @@ configuration.</p>
 </section>
 <section id="axolotl.train.setup_model_and_trainer" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.setup_model_and_trainer">setup_model_and_trainer</h3>
-<div class="sourceCode" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>train.setup_model_and_trainer(cfg, dataset_meta)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>train.setup_model_and_trainer(cfg, dataset_meta)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Load model, tokenizer, trainer, etc. Helper function to encapsulate the full
 trainer setup.</p>
-<section id="parameters-7" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-7">Parameters</h4>
+<section id="parameters-6" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-6">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 13%">
@@ -977,8 +916,8 @@ trainer setup.</p>
 </tbody>
 </table>
 </section>
-<section id="returns-2" class="level4 doc-section doc-section-returns">
-<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns-2">Returns</h4>
+<section id="returns-1" class="level4 doc-section doc-section-returns">
+<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns-1">Returns</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 3%">
@@ -1004,10 +943,10 @@ trainer setup.</p>
 </section>
 <section id="axolotl.train.setup_model_card" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.setup_model_card">setup_model_card</h3>
-<div class="sourceCode" id="cb9"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a>train.setup_model_card(cfg)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>train.setup_model_card(cfg)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Set up the Axolotl badge and add the Axolotl config to the model card if available.</p>
-<section id="parameters-8" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-8">Parameters</h4>
+<section id="parameters-7" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-7">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 9%">
@@ -1036,10 +975,10 @@ trainer setup.</p>
 </section>
 <section id="axolotl.train.setup_reference_model" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.setup_reference_model">setup_reference_model</h3>
-<div class="sourceCode" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>train.setup_reference_model(cfg, tokenizer)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb9"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a>train.setup_reference_model(cfg, tokenizer)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Set up the reference model for RL training if needed.</p>
-<section id="parameters-9" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-9">Parameters</h4>
+<section id="parameters-8" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-8">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 11%">
@@ -1071,8 +1010,8 @@ trainer setup.</p>
 </tbody>
 </table>
 </section>
-<section id="returns-3" class="level4 doc-section doc-section-returns">
-<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns-3">Returns</h4>
+<section id="returns-2" class="level4 doc-section doc-section-returns">
+<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns-2">Returns</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 8%">
@@ -1098,10 +1037,10 @@ trainer setup.</p>
 </section>
 <section id="axolotl.train.setup_signal_handler" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.setup_signal_handler">setup_signal_handler</h3>
-<div class="sourceCode" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>train.setup_signal_handler(cfg, model, safe_serialization)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>train.setup_signal_handler(cfg, model, safe_serialization)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Set up signal handler for graceful termination.</p>
-<section id="parameters-10" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-10">Parameters</h4>
+<section id="parameters-9" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-9">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 19%">
@@ -1142,10 +1081,10 @@ trainer setup.</p>
 </section>
 <section id="axolotl.train.train" class="level3">
 <h3 class="anchored" data-anchor-id="axolotl.train.train">train</h3>
-<div class="sourceCode" id="cb12"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a>train.train(cfg, dataset_meta)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>train.train(cfg, dataset_meta)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Train a model on the given dataset.</p>
-<section id="parameters-11" class="level4 doc-section doc-section-parameters">
-<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-11">Parameters</h4>
+<section id="parameters-10" class="level4 doc-section doc-section-parameters">
+<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-10">Parameters</h4>
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@@ -1177,8 +1116,8 @@ trainer setup.</p>
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-<section id="returns-4" class="level4 doc-section doc-section-returns">
-<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns-4">Returns</h4>
+<section id="returns-3" class="level4 doc-section doc-section-returns">
+<h4 class="doc-section doc-section-returns anchored" data-anchor-id="returns-3">Returns</h4>
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diff --git a/search.json b/search.json
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@@ -2989,14 +2989,14 @@
     "href": "docs/api/train.html",
     "title": "train",
     "section": "",
-    "text": "train\nPrepare and train a model on a dataset. Can also infer from a model or merge lora\n\n\n\n\n\nName\nDescription\n\n\n\n\ncreate_model_card\nCreate a model card for the trained model if needed.\n\n\ndetermine_resume_checkpoint\nDetermine the checkpoint to resume from based on configuration.\n\n\nexecute_training\nExecute the training process with appropriate SDP kernel configurations.\n\n\nhandle_untrained_tokens_fix\nApply fixes for untrained tokens if configured.\n\n\nsave_initial_configs\nSave initial configurations before training.\n\n\nsave_trained_model\nSave the trained model according to configuration and training setup.\n\n\nsetup_model_and_tokenizer\nLoad the tokenizer, processor (for multimodal models), and model based on\n\n\nsetup_model_and_trainer\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\n\n\nsetup_model_card\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\nsetup_reference_model\nSet up the reference model for RL training if needed.\n\n\nsetup_signal_handler\nSet up signal handler for graceful termination.\n\n\ntrain\nTrain a model on the given dataset.\n\n\n\n\n\ntrain.create_model_card(cfg, trainer)\nCreate a model card for the trained model if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nTrainer\nThe trainer object with model card creation capabilities.\nrequired\n\n\n\n\n\n\n\ntrain.determine_resume_checkpoint(cfg)\nDetermine the checkpoint to resume from based on configuration.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\nstr | None\nPath to the checkpoint to resume from, or None if not resuming.\n\n\n\n\n\n\n\ntrain.execute_training(cfg, trainer, resume_from_checkpoint)\nExecute the training process with appropriate SDP kernel configurations.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe configured trainer object.\nrequired\n\n\nresume_from_checkpoint\nstr | None\nPath to checkpoint to resume from, if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.handle_untrained_tokens_fix(\n    cfg,\n    model,\n    tokenizer,\n    train_dataset,\n    safe_serialization,\n)\nApply fixes for untrained tokens if configured.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to apply fixes to.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer for token identification.\nrequired\n\n\ntrain_dataset\nDataset\nThe training dataset to use.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving.\nrequired\n\n\n\n\n\n\n\ntrain.save_initial_configs(cfg, tokenizer, model, peft_config, processor)\nSave initial configurations before training.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to save.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save configuration for.\nrequired\n\n\npeft_config\nPeftConfig | None\nThe PEFT configuration to save if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.save_trained_model(cfg, trainer, model, safe_serialization)\nSave the trained model according to configuration and training setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe trainer object.\nrequired\n\n\nmodel\nPreTrainedModel\nThe trained model to save.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization.\nrequired\n\n\n\n\n\n\n\ntrain.setup_model_and_tokenizer(cfg)\nLoad the tokenizer, processor (for multimodal models), and model based on\nconfiguration.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple containing model, tokenizer, peft_config (if LoRA / QLoRA, else None), and processor (if multimodal, else None).\n\n\n\n\n\n\n\ntrain.setup_model_and_trainer(cfg, dataset_meta)\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\ntrainer setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters.\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple['HFRLTrainerBuilder' | 'HFCausalTrainerBuilder', PeftModel | PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple of: - Trainer (Causal or RLHF) - Model - Tokenizer - PEFT config - Processor\n\n\n\n\n\n\n\ntrain.setup_model_card(cfg)\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\ntrain.setup_reference_model(cfg, tokenizer)\nSet up the reference model for RL training if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to use for the reference model.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\nPreTrainedModel | None\nReference model if needed for RL training, None otherwise.\n\n\n\n\n\n\n\ntrain.setup_signal_handler(cfg, model, safe_serialization)\nSet up signal handler for graceful termination.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save on termination\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving\nrequired\n\n\n\n\n\n\n\ntrain.train(cfg, dataset_meta)\nTrain a model on the given dataset.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PeftModel | PreTrainedModel, PreTrainedTokenizer, Trainer]\nTuple of (model, tokenizer) after training"
+    "text": "train\nPrepare and train a model on a dataset. Can also infer from a model or merge lora\n\n\n\n\n\nName\nDescription\n\n\n\n\ncreate_model_card\nCreate a model card for the trained model if needed.\n\n\nexecute_training\nExecute the training process with appropriate SDP kernel configurations.\n\n\nhandle_untrained_tokens_fix\nApply fixes for untrained tokens if configured.\n\n\nsave_initial_configs\nSave initial configurations before training.\n\n\nsave_trained_model\nSave the trained model according to configuration and training setup.\n\n\nsetup_model_and_tokenizer\nLoad the tokenizer, processor (for multimodal models), and model based on\n\n\nsetup_model_and_trainer\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\n\n\nsetup_model_card\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\nsetup_reference_model\nSet up the reference model for RL training if needed.\n\n\nsetup_signal_handler\nSet up signal handler for graceful termination.\n\n\ntrain\nTrain a model on the given dataset.\n\n\n\n\n\ntrain.create_model_card(cfg, trainer)\nCreate a model card for the trained model if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nTrainer\nThe trainer object with model card creation capabilities.\nrequired\n\n\n\n\n\n\n\ntrain.execute_training(cfg, trainer, resume_from_checkpoint)\nExecute the training process with appropriate SDP kernel configurations.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe configured trainer object.\nrequired\n\n\nresume_from_checkpoint\nstr | None\nPath to checkpoint to resume from, if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.handle_untrained_tokens_fix(\n    cfg,\n    model,\n    tokenizer,\n    train_dataset,\n    safe_serialization,\n)\nApply fixes for untrained tokens if configured.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to apply fixes to.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer for token identification.\nrequired\n\n\ntrain_dataset\nDataset\nThe training dataset to use.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving.\nrequired\n\n\n\n\n\n\n\ntrain.save_initial_configs(cfg, tokenizer, model, peft_config, processor)\nSave initial configurations before training.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to save.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save configuration for.\nrequired\n\n\npeft_config\nPeftConfig | None\nThe PEFT configuration to save if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.save_trained_model(cfg, trainer, model, safe_serialization)\nSave the trained model according to configuration and training setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe trainer object.\nrequired\n\n\nmodel\nPreTrainedModel\nThe trained model to save.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization.\nrequired\n\n\n\n\n\n\n\ntrain.setup_model_and_tokenizer(cfg)\nLoad the tokenizer, processor (for multimodal models), and model based on\nconfiguration.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple containing model, tokenizer, peft_config (if LoRA / QLoRA, else None), and processor (if multimodal, else None).\n\n\n\n\n\n\n\ntrain.setup_model_and_trainer(cfg, dataset_meta)\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\ntrainer setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters.\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple['HFRLTrainerBuilder' | 'HFCausalTrainerBuilder', PeftModel | PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple of: - Trainer (Causal or RLHF) - Model - Tokenizer - PEFT config - Processor\n\n\n\n\n\n\n\ntrain.setup_model_card(cfg)\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\ntrain.setup_reference_model(cfg, tokenizer)\nSet up the reference model for RL training if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to use for the reference model.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\nPreTrainedModel | None\nReference model if needed for RL training, None otherwise.\n\n\n\n\n\n\n\ntrain.setup_signal_handler(cfg, model, safe_serialization)\nSet up signal handler for graceful termination.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save on termination\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving\nrequired\n\n\n\n\n\n\n\ntrain.train(cfg, dataset_meta)\nTrain a model on the given dataset.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PeftModel | PreTrainedModel, PreTrainedTokenizer, Trainer]\nTuple of (model, tokenizer) after training"
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     "objectID": "docs/api/train.html#functions",
     "href": "docs/api/train.html#functions",
     "title": "train",
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-    "text": "Name\nDescription\n\n\n\n\ncreate_model_card\nCreate a model card for the trained model if needed.\n\n\ndetermine_resume_checkpoint\nDetermine the checkpoint to resume from based on configuration.\n\n\nexecute_training\nExecute the training process with appropriate SDP kernel configurations.\n\n\nhandle_untrained_tokens_fix\nApply fixes for untrained tokens if configured.\n\n\nsave_initial_configs\nSave initial configurations before training.\n\n\nsave_trained_model\nSave the trained model according to configuration and training setup.\n\n\nsetup_model_and_tokenizer\nLoad the tokenizer, processor (for multimodal models), and model based on\n\n\nsetup_model_and_trainer\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\n\n\nsetup_model_card\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\nsetup_reference_model\nSet up the reference model for RL training if needed.\n\n\nsetup_signal_handler\nSet up signal handler for graceful termination.\n\n\ntrain\nTrain a model on the given dataset.\n\n\n\n\n\ntrain.create_model_card(cfg, trainer)\nCreate a model card for the trained model if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nTrainer\nThe trainer object with model card creation capabilities.\nrequired\n\n\n\n\n\n\n\ntrain.determine_resume_checkpoint(cfg)\nDetermine the checkpoint to resume from based on configuration.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\nstr | None\nPath to the checkpoint to resume from, or None if not resuming.\n\n\n\n\n\n\n\ntrain.execute_training(cfg, trainer, resume_from_checkpoint)\nExecute the training process with appropriate SDP kernel configurations.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe configured trainer object.\nrequired\n\n\nresume_from_checkpoint\nstr | None\nPath to checkpoint to resume from, if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.handle_untrained_tokens_fix(\n    cfg,\n    model,\n    tokenizer,\n    train_dataset,\n    safe_serialization,\n)\nApply fixes for untrained tokens if configured.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to apply fixes to.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer for token identification.\nrequired\n\n\ntrain_dataset\nDataset\nThe training dataset to use.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving.\nrequired\n\n\n\n\n\n\n\ntrain.save_initial_configs(cfg, tokenizer, model, peft_config, processor)\nSave initial configurations before training.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to save.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save configuration for.\nrequired\n\n\npeft_config\nPeftConfig | None\nThe PEFT configuration to save if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.save_trained_model(cfg, trainer, model, safe_serialization)\nSave the trained model according to configuration and training setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe trainer object.\nrequired\n\n\nmodel\nPreTrainedModel\nThe trained model to save.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization.\nrequired\n\n\n\n\n\n\n\ntrain.setup_model_and_tokenizer(cfg)\nLoad the tokenizer, processor (for multimodal models), and model based on\nconfiguration.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple containing model, tokenizer, peft_config (if LoRA / QLoRA, else None), and processor (if multimodal, else None).\n\n\n\n\n\n\n\ntrain.setup_model_and_trainer(cfg, dataset_meta)\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\ntrainer setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters.\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple['HFRLTrainerBuilder' | 'HFCausalTrainerBuilder', PeftModel | PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple of: - Trainer (Causal or RLHF) - Model - Tokenizer - PEFT config - Processor\n\n\n\n\n\n\n\ntrain.setup_model_card(cfg)\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\ntrain.setup_reference_model(cfg, tokenizer)\nSet up the reference model for RL training if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to use for the reference model.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\nPreTrainedModel | None\nReference model if needed for RL training, None otherwise.\n\n\n\n\n\n\n\ntrain.setup_signal_handler(cfg, model, safe_serialization)\nSet up signal handler for graceful termination.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save on termination\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving\nrequired\n\n\n\n\n\n\n\ntrain.train(cfg, dataset_meta)\nTrain a model on the given dataset.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PeftModel | PreTrainedModel, PreTrainedTokenizer, Trainer]\nTuple of (model, tokenizer) after training"
+    "text": "Name\nDescription\n\n\n\n\ncreate_model_card\nCreate a model card for the trained model if needed.\n\n\nexecute_training\nExecute the training process with appropriate SDP kernel configurations.\n\n\nhandle_untrained_tokens_fix\nApply fixes for untrained tokens if configured.\n\n\nsave_initial_configs\nSave initial configurations before training.\n\n\nsave_trained_model\nSave the trained model according to configuration and training setup.\n\n\nsetup_model_and_tokenizer\nLoad the tokenizer, processor (for multimodal models), and model based on\n\n\nsetup_model_and_trainer\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\n\n\nsetup_model_card\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\nsetup_reference_model\nSet up the reference model for RL training if needed.\n\n\nsetup_signal_handler\nSet up signal handler for graceful termination.\n\n\ntrain\nTrain a model on the given dataset.\n\n\n\n\n\ntrain.create_model_card(cfg, trainer)\nCreate a model card for the trained model if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nTrainer\nThe trainer object with model card creation capabilities.\nrequired\n\n\n\n\n\n\n\ntrain.execute_training(cfg, trainer, resume_from_checkpoint)\nExecute the training process with appropriate SDP kernel configurations.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe configured trainer object.\nrequired\n\n\nresume_from_checkpoint\nstr | None\nPath to checkpoint to resume from, if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.handle_untrained_tokens_fix(\n    cfg,\n    model,\n    tokenizer,\n    train_dataset,\n    safe_serialization,\n)\nApply fixes for untrained tokens if configured.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to apply fixes to.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer for token identification.\nrequired\n\n\ntrain_dataset\nDataset\nThe training dataset to use.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving.\nrequired\n\n\n\n\n\n\n\ntrain.save_initial_configs(cfg, tokenizer, model, peft_config, processor)\nSave initial configurations before training.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to save.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save configuration for.\nrequired\n\n\npeft_config\nPeftConfig | None\nThe PEFT configuration to save if applicable.\nrequired\n\n\n\n\n\n\n\ntrain.save_trained_model(cfg, trainer, model, safe_serialization)\nSave the trained model according to configuration and training setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntrainer\nAny\nThe trainer object.\nrequired\n\n\nmodel\nPreTrainedModel\nThe trained model to save.\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization.\nrequired\n\n\n\n\n\n\n\ntrain.setup_model_and_tokenizer(cfg)\nLoad the tokenizer, processor (for multimodal models), and model based on\nconfiguration.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple containing model, tokenizer, peft_config (if LoRA / QLoRA, else None), and processor (if multimodal, else None).\n\n\n\n\n\n\n\ntrain.setup_model_and_trainer(cfg, dataset_meta)\nLoad model, tokenizer, trainer, etc. Helper function to encapsulate the full\ntrainer setup.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters.\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple['HFRLTrainerBuilder' | 'HFCausalTrainerBuilder', PeftModel | PreTrainedModel, PreTrainedTokenizer, PeftConfig | None, ProcessorMixin | None]\nTuple of: - Trainer (Causal or RLHF) - Model - Tokenizer - PEFT config - Processor\n\n\n\n\n\n\n\ntrain.setup_model_card(cfg)\nSet up the Axolotl badge and add the Axolotl config to the model card if available.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\n\n\n\n\n\ntrain.setup_reference_model(cfg, tokenizer)\nSet up the reference model for RL training if needed.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\ntokenizer\nPreTrainedTokenizer\nThe tokenizer to use for the reference model.\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\nPreTrainedModel | None\nReference model if needed for RL training, None otherwise.\n\n\n\n\n\n\n\ntrain.setup_signal_handler(cfg, model, safe_serialization)\nSet up signal handler for graceful termination.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nDictionary mapping axolotl config keys to values.\nrequired\n\n\nmodel\nPreTrainedModel\nThe model to save on termination\nrequired\n\n\nsafe_serialization\nbool\nWhether to use safe serialization when saving\nrequired\n\n\n\n\n\n\n\ntrain.train(cfg, dataset_meta)\nTrain a model on the given dataset.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ncfg\nDictDefault\nThe configuration dictionary with training parameters\nrequired\n\n\ndataset_meta\nTrainDatasetMeta\nObject with training, validation datasets and metadata\nrequired\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\n\n\n\n\n\ntuple[PeftModel | PreTrainedModel, PreTrainedTokenizer, Trainer]\nTuple of (model, tokenizer) after training"
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diff --git a/sitemap.xml b/sitemap.xml
index f47fbc153..d92f4214c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
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