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@@ -593,7 +593,8 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
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<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a> quantize_embedding<span class="op">=</span><span class="va">None</span>,</span>
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<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a> group_size<span class="op">=</span><span class="va">None</span>,</span>
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<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a> output_dir<span class="op">=</span><span class="va">None</span>,</span>
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<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a> hub_model_id<span class="op">=</span><span class="va">None</span>,</span>
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<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>Dataclass with CLI arguments for <code>axolotl quantize</code> command.</p>
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</section>
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<section id="axolotl.cli.args.TrainerCliArgs" class="level3">
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@@ -501,10 +501,10 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
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<ul class="collapse">
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<li><a href="#functions" id="toc-functions" class="nav-link" data-scroll-target="#functions">Functions</a>
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<ul class="collapse">
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<li><a href="#axolotl.utils.quantization.convert_qat_model_for_ptq" id="toc-axolotl.utils.quantization.convert_qat_model_for_ptq" class="nav-link" data-scroll-target="#axolotl.utils.quantization.convert_qat_model_for_ptq">convert_qat_model_for_ptq</a></li>
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<li><a href="#axolotl.utils.quantization.get_ptq_config" id="toc-axolotl.utils.quantization.get_ptq_config" class="nav-link" data-scroll-target="#axolotl.utils.quantization.get_ptq_config">get_ptq_config</a></li>
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<li><a href="#axolotl.utils.quantization.convert_qat_model" id="toc-axolotl.utils.quantization.convert_qat_model" class="nav-link" data-scroll-target="#axolotl.utils.quantization.convert_qat_model">convert_qat_model</a></li>
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<li><a href="#axolotl.utils.quantization.get_quantization_config" id="toc-axolotl.utils.quantization.get_quantization_config" class="nav-link" data-scroll-target="#axolotl.utils.quantization.get_quantization_config">get_quantization_config</a></li>
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<li><a href="#axolotl.utils.quantization.prepare_model_for_qat" id="toc-axolotl.utils.quantization.prepare_model_for_qat" class="nav-link" data-scroll-target="#axolotl.utils.quantization.prepare_model_for_qat">prepare_model_for_qat</a></li>
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<li><a href="#axolotl.utils.quantization.quantize_model_for_ptq" id="toc-axolotl.utils.quantization.quantize_model_for_ptq" class="nav-link" data-scroll-target="#axolotl.utils.quantization.quantize_model_for_ptq">quantize_model_for_ptq</a></li>
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<li><a href="#axolotl.utils.quantization.quantize_model" id="toc-axolotl.utils.quantization.quantize_model" class="nav-link" data-scroll-target="#axolotl.utils.quantization.quantize_model">quantize_model</a></li>
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</ul></li>
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</ul></li>
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</ul>
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@@ -531,11 +531,11 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
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</thead>
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<tbody>
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<tr class="odd">
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<td><a href="#axolotl.utils.quantization.convert_qat_model_for_ptq">convert_qat_model_for_ptq</a></td>
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<td>This function is used to convert a swap fake-quantized modules in a model</td>
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<td><a href="#axolotl.utils.quantization.convert_qat_model">convert_qat_model</a></td>
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<td>This function converts a QAT model which has fake quantized layers back to the original model.</td>
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</tr>
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<tr class="even">
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<td><a href="#axolotl.utils.quantization.get_ptq_config">get_ptq_config</a></td>
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<td><a href="#axolotl.utils.quantization.get_quantization_config">get_quantization_config</a></td>
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<td>This function is used to build a post-training quantization config.</td>
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</tr>
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<tr class="odd">
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@@ -543,65 +543,31 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
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<td>This function is used to prepare a model for QAT by swapping the model’s linear</td>
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</tr>
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<tr class="even">
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<td><a href="#axolotl.utils.quantization.quantize_model_for_ptq">quantize_model_for_ptq</a></td>
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<td>This function is used to quantize a model for post-training quantization.</td>
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</tr>
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</tbody>
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</table>
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<section id="axolotl.utils.quantization.convert_qat_model_for_ptq" class="level3">
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<h3 class="anchored" data-anchor-id="axolotl.utils.quantization.convert_qat_model_for_ptq">convert_qat_model_for_ptq</h3>
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<div class="sourceCode" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>utils.quantization.convert_qat_model_for_ptq(model, <span class="op">*</span>, quantize_embedding<span class="op">=</span><span class="va">None</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>This function is used to convert a swap fake-quantized modules in a model
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which has been trained with QAT back to the original modules, ready for PTQ.</p>
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<section id="parameters" class="level4 doc-section doc-section-parameters">
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<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters">Parameters</h4>
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<table class="caption-top table">
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<colgroup>
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<col style="width: 20%">
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<col style="width: 14%">
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<col style="width: 53%">
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<col style="width: 12%">
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</colgroup>
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<thead>
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<tr class="header">
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<th>Name</th>
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<th>Type</th>
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<th>Description</th>
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<th>Default</th>
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</tr>
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</thead>
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<tbody>
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<tr class="odd">
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<td>model</td>
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<td></td>
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<td>The model to convert.</td>
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<td><em>required</em></td>
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</tr>
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<tr class="even">
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<td>quantize_embedding</td>
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<td>bool | None</td>
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<td>Whether to quantize the model’s embedding weights.</td>
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<td><code>None</code></td>
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<td><a href="#axolotl.utils.quantization.quantize_model">quantize_model</a></td>
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<td>This function is used to quantize a model.</td>
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</tr>
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</tbody>
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</table>
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<section id="axolotl.utils.quantization.convert_qat_model" class="level3">
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<h3 class="anchored" data-anchor-id="axolotl.utils.quantization.convert_qat_model">convert_qat_model</h3>
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<div class="sourceCode" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>utils.quantization.convert_qat_model(model, quantize_embedding<span class="op">=</span><span class="va">False</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
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<p>This function converts a QAT model which has fake quantized layers back to the original model.</p>
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</section>
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</section>
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<section id="axolotl.utils.quantization.get_ptq_config" class="level3">
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<h3 class="anchored" data-anchor-id="axolotl.utils.quantization.get_ptq_config">get_ptq_config</h3>
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<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>utils.quantization.get_ptq_config(</span>
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<section id="axolotl.utils.quantization.get_quantization_config" class="level3">
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<h3 class="anchored" data-anchor-id="axolotl.utils.quantization.get_quantization_config">get_quantization_config</h3>
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<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>utils.quantization.get_quantization_config(</span>
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<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a> weight_dtype,</span>
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<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a> activation_dtype<span class="op">=</span><span class="va">None</span>,</span>
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<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a> group_size<span class="op">=</span><span class="va">None</span>,</span>
|
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<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>This function is used to build a post-training quantization config.</p>
|
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<section id="parameters-1" class="level4 doc-section doc-section-parameters">
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<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters-1">Parameters</h4>
|
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<section id="parameters" class="level4 doc-section doc-section-parameters">
|
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<h4 class="doc-section doc-section-parameters anchored" data-anchor-id="parameters">Parameters</h4>
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<table class="caption-top table">
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<colgroup>
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<col style="width: 17%">
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<col style="width: 22%">
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<col style="width: 47%">
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<col style="width: 25%">
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<col style="width: 45%">
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<col style="width: 11%">
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</colgroup>
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<thead>
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@@ -615,13 +581,13 @@ which has been trained with QAT back to the original modules, ready for PTQ.</p>
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<tbody>
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<tr class="odd">
|
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<td>weight_dtype</td>
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<td>TorchIntDType</td>
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<td>TorchAOQuantDType</td>
|
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<td>The dtype to use for weight quantization.</td>
|
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<td><em>required</em></td>
|
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</tr>
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<tr class="even">
|
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<td>activation_dtype</td>
|
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<td>TorchIntDType | None</td>
|
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<td>TorchAOQuantDType | None</td>
|
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<td>The dtype to use for activation quantization.</td>
|
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<td><code>None</code></td>
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</tr>
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@@ -683,21 +649,21 @@ which has been trained with QAT back to the original modules, ready for PTQ.</p>
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<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>utils.quantization.prepare_model_for_qat(</span>
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<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a> model,</span>
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<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a> weight_dtype,</span>
|
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<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a> group_size,</span>
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<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a> group_size<span class="op">=</span><span class="va">None</span>,</span>
|
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<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a> activation_dtype<span class="op">=</span><span class="va">None</span>,</span>
|
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<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a> quantize_embedding<span class="op">=</span><span class="va">False</span>,</span>
|
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<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>This function is used to prepare a model for QAT by swapping the model’s linear
|
||||
layers with fake quantized linear layers, and optionally the embedding weights with
|
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fake quantized embedding weights.</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>
|
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<table class="caption-top table">
|
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<colgroup>
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<col style="width: 18%">
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<col style="width: 21%">
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<col style="width: 48%">
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<col style="width: 11%">
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<col style="width: 24%">
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<col style="width: 46%">
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<col style="width: 10%">
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</colgroup>
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<thead>
|
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<tr class="header">
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@@ -716,19 +682,19 @@ fake quantized embedding weights.</p>
|
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</tr>
|
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<tr class="even">
|
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<td>weight_dtype</td>
|
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<td>TorchIntDType</td>
|
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<td>TorchAOQuantDType</td>
|
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<td>The dtype to use for weight quantization.</td>
|
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<td><em>required</em></td>
|
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</tr>
|
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<tr class="odd">
|
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<td>group_size</td>
|
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<td>int</td>
|
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<td>int | None</td>
|
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<td>The group size to use for weight quantization.</td>
|
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<td><em>required</em></td>
|
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<td><code>None</code></td>
|
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</tr>
|
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<tr class="even">
|
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<td>activation_dtype</td>
|
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<td>TorchIntDType | None</td>
|
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<td>TorchAOQuantDType | None</td>
|
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<td>The dtype to use for activation quantization.</td>
|
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<td><code>None</code></td>
|
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</tr>
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@@ -766,26 +732,24 @@ fake quantized embedding weights.</p>
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</table>
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</section>
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</section>
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<section id="axolotl.utils.quantization.quantize_model_for_ptq" class="level3">
|
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<h3 class="anchored" data-anchor-id="axolotl.utils.quantization.quantize_model_for_ptq">quantize_model_for_ptq</h3>
|
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<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>utils.quantization.quantize_model_for_ptq(</span>
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<section id="axolotl.utils.quantization.quantize_model" class="level3">
|
||||
<h3 class="anchored" data-anchor-id="axolotl.utils.quantization.quantize_model">quantize_model</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>utils.quantization.quantize_model(</span>
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<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a> model,</span>
|
||||
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a> weight_dtype,</span>
|
||||
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a> group_size<span class="op">=</span><span class="va">None</span>,</span>
|
||||
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a> activation_dtype<span class="op">=</span><span class="va">None</span>,</span>
|
||||
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a> quantize_embedding<span class="op">=</span><span class="va">None</span>,</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>
|
||||
<p>This function is used to quantize a model for post-training quantization.
|
||||
It swaps the model’s linear layers with fake quantized linear layers.
|
||||
If <code>quantize_embedding</code> is True, it will also swap the model’s embedding weights with fake quantized embedding weights.</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>
|
||||
<p>This function is used to quantize a model.</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>
|
||||
<table class="caption-top table">
|
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<colgroup>
|
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<col style="width: 18%">
|
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<col style="width: 21%">
|
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<col style="width: 48%">
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<col style="width: 11%">
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<col style="width: 24%">
|
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<col style="width: 46%">
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<col style="width: 10%">
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</colgroup>
|
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<thead>
|
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<tr class="header">
|
||||
@@ -804,7 +768,7 @@ If <code>quantize_embedding</code> is True, it will also swap the model’s embe
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td>weight_dtype</td>
|
||||
<td>TorchIntDType</td>
|
||||
<td>TorchAOQuantDType</td>
|
||||
<td>The dtype to use for weight quantization.</td>
|
||||
<td><em>required</em></td>
|
||||
</tr>
|
||||
@@ -816,7 +780,7 @@ If <code>quantize_embedding</code> is True, it will also swap the model’s embe
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td>activation_dtype</td>
|
||||
<td>TorchIntDType | None</td>
|
||||
<td>TorchAOQuantDType | None</td>
|
||||
<td>The dtype to use for activation quantization.</td>
|
||||
<td><code>None</code></td>
|
||||
</tr>
|
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|
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@@ -505,7 +505,6 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
|
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<li><a href="#axolotl.utils.schemas.enums.CustomSupportedOptimizers" id="toc-axolotl.utils.schemas.enums.CustomSupportedOptimizers" class="nav-link" data-scroll-target="#axolotl.utils.schemas.enums.CustomSupportedOptimizers">CustomSupportedOptimizers</a></li>
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||||
<li><a href="#axolotl.utils.schemas.enums.RLType" id="toc-axolotl.utils.schemas.enums.RLType" class="nav-link" data-scroll-target="#axolotl.utils.schemas.enums.RLType">RLType</a></li>
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||||
<li><a href="#axolotl.utils.schemas.enums.RingAttnFunc" id="toc-axolotl.utils.schemas.enums.RingAttnFunc" class="nav-link" data-scroll-target="#axolotl.utils.schemas.enums.RingAttnFunc">RingAttnFunc</a></li>
|
||||
<li><a href="#axolotl.utils.schemas.enums.TorchIntDType" id="toc-axolotl.utils.schemas.enums.TorchIntDType" class="nav-link" data-scroll-target="#axolotl.utils.schemas.enums.TorchIntDType">TorchIntDType</a></li>
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</ul></li>
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</ul></li>
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</ul>
|
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@@ -547,10 +546,6 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
|
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<td><a href="#axolotl.utils.schemas.enums.RingAttnFunc">RingAttnFunc</a></td>
|
||||
<td>Enum class for supported <code>ring-flash-attn</code> implementations</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td><a href="#axolotl.utils.schemas.enums.TorchIntDType">TorchIntDType</a></td>
|
||||
<td>Torch integer data types - <code>getattr</code> guards against torch < 2.6 which does not support int4</td>
|
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</tr>
|
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</tbody>
|
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</table>
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<section id="axolotl.utils.schemas.enums.ChatTemplate" class="level3">
|
||||
@@ -572,11 +567,6 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
|
||||
<h3 class="anchored" data-anchor-id="axolotl.utils.schemas.enums.RingAttnFunc">RingAttnFunc</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>utils.schemas.enums.RingAttnFunc()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||||
<p>Enum class for supported <code>ring-flash-attn</code> implementations</p>
|
||||
</section>
|
||||
<section id="axolotl.utils.schemas.enums.TorchIntDType" class="level3">
|
||||
<h3 class="anchored" data-anchor-id="axolotl.utils.schemas.enums.TorchIntDType">TorchIntDType</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>utils.schemas.enums.TorchIntDType()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||||
<p>Torch integer data types - <code>getattr</code> guards against torch < 2.6 which does not support int4</p>
|
||||
|
||||
|
||||
</section>
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -561,6 +561,20 @@ you used to train the model:</p>
|
||||
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a><span class="fu">output_dir</span><span class="kw">:</span><span class="co"> # The path to the output directory used during training where the final checkpoint has been saved.</span></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 bash code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="ex">axolotl</span> quantize qat.yml</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||||
<p>This ensures that an identical quantization configuration is used to quantize the model as was used to train it.</p>
|
||||
<div class="callout callout-style-default callout-note callout-titled">
|
||||
<div class="callout-header d-flex align-content-center">
|
||||
<div class="callout-icon-container">
|
||||
<i class="callout-icon"></i>
|
||||
</div>
|
||||
<div class="callout-title-container flex-fill">
|
||||
Note
|
||||
</div>
|
||||
</div>
|
||||
<div class="callout-body-container callout-body">
|
||||
<p>If you have configured pushing to hub with <code>hub_model_id</code>, your model hub name will have the quantization schema appended to it,
|
||||
e.g. <code>axolotl-ai-cloud/qat-nvfp4-llama3B</code> will become <code>axolotl-ai-cloud/qat-nvfp4-llama3B-nvfp4w</code></p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
</section>
|
||||
|
||||
20
index.html
20
index.html
@@ -499,7 +499,7 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
|
||||
<ul>
|
||||
<li><a href="#latest-updates" id="toc-latest-updates" class="nav-link active" data-scroll-target="#latest-updates">🎉 Latest Updates</a></li>
|
||||
<li><a href="#overview" id="toc-overview" class="nav-link" data-scroll-target="#overview">✨ Overview</a></li>
|
||||
<li><a href="#quick-start" id="toc-quick-start" class="nav-link" data-scroll-target="#quick-start">🚀 Quick Start</a>
|
||||
<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>
|
||||
<ul class="collapse">
|
||||
<li><a href="#google-colab" id="toc-google-colab" class="nav-link" data-scroll-target="#google-colab">Google Colab</a></li>
|
||||
<li><a href="#installation" id="toc-installation" class="nav-link" data-scroll-target="#installation">Installation</a></li>
|
||||
@@ -528,6 +528,9 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
|
||||
</picture>
|
||||
</p>
|
||||
<p align="center">
|
||||
<strong>A Free and Open Source LLM Fine-tuning Framework</strong><br>
|
||||
</p>
|
||||
<p align="center">
|
||||
<img src="https://img.shields.io/github/license/axolotl-ai-cloud/axolotl.svg?color=blue" alt="GitHub License">
|
||||
<img src="https://github.com/axolotl-ai-cloud/axolotl/actions/workflows/tests.yml/badge.svg" alt="tests">
|
||||
<a href="https://codecov.io/gh/axolotl-ai-cloud/axolotl"><img src="https://codecov.io/gh/axolotl-ai-cloud/axolotl/branch/main/graph/badge.svg" alt="codecov"></a>
|
||||
@@ -573,19 +576,20 @@ Expand older updates
|
||||
</section>
|
||||
<section id="overview" class="level2">
|
||||
<h2 class="anchored" data-anchor-id="overview">✨ Overview</h2>
|
||||
<p>Axolotl is a tool designed to streamline post-training for various AI models.</p>
|
||||
<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 LLaMA, Mistral, Mixtral, Pythia, and more. We are compatible with HuggingFace transformers causal language models.</li>
|
||||
<li><strong>Training Methods</strong>: Full fine-tuning, LoRA, QLoRA, GPTQ, QAT, Preference Tuning (DPO, IPO, KTO, ORPO), RL (GRPO), Multimodal, and Reward Modelling (RM) / Process Reward Modelling (PRM).</li>
|
||||
<li><strong>Easy Configuration</strong>: Re-use a single YAML file between dataset preprocess, training, evaluation, quantization, and inference.</li>
|
||||
<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" class="level2">
|
||||
<h2 class="anchored" data-anchor-id="quick-start">🚀 Quick Start</h2>
|
||||
<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>
|
||||
@@ -681,7 +685,7 @@ Expand older updates
|
||||
<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: Post-Training for AI Models},</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>
|
||||
|
||||
38
search.json
38
search.json
File diff suppressed because one or more lines are too long
396
sitemap.xml
396
sitemap.xml
@@ -2,794 +2,794 @@
|
||||
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/examples/colab-notebooks/colab-axolotl-example.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.176Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.656Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/src/axolotl/integrations/LICENSE.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.193Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.673Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/FAQS.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.166Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.646Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/unsloth.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.653Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/reward_modelling.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/docker.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.168Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.649Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/batch_vs_grad.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.168Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.648Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/streaming.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/nccl.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/quantize.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/nd_parallelism.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/custom_integrations.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.168Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.648Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/debugging.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.168Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.649Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/gradient_checkpointing.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.169Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.649Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/multimodal.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/dataset_loading.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.168Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.648Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/integrations.spectrum.args.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.774Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.604Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/loaders.adapter.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.897Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.753Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/core.builders.base.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.533Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.394Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.merge_sharded_fsdp_weights.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.735Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.592Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.cloud.modal_.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.765Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.621Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/monkeypatch.stablelm_attn_hijack_flash.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.315Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.169Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/integrations.kd.trainer.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.764Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.594Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.delinearize_llama4.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.700Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.558Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.evaluate.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.648Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.506Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/utils.schemas.model.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.529Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.376Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.art.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.671Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.529Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.dpo.llama3.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.083Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.935Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/core.chat.format.llama3x.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.581Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.441Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.kto.chatml.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.114Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.966Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.args.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.668Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.525Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/monkeypatch.gradient_checkpointing.offload_cpu.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.340Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.194Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/evaluate.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.456Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.316Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.input_output.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.046Z</lastmod>
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<lastmod>2025-09-12T10:00:00.110Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/utils.callbacks.lisa.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.872Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.703Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/monkeypatch.data.batch_dataset_fetcher.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.335Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.189Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/core.trainers.mixins.optimizer.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.919Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.770Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/loaders.processor.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.891Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.748Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/core.trainers.utils.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.872Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.728Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.dpo.chat_template.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.073Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.925Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_tokenizers.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.517Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.378Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/utils.callbacks.comet_.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.879Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.710Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/core.datasets.transforms.chat_builder.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.595Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.455Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/utils.trainer.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.413Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.267Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.train.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.640Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.497Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/integrations.lm_eval.args.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.770Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.601Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.messages.chat.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.072Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.923Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/utils.schemas.peft.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.562Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.410Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.bradley_terry.llama3.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.140Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.992Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/cli.utils.args.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.778Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.634Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.stepwise_supervised.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.050Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.902Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/common.datasets.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.791Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:00.622Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/prompt_strategies.kto.user_defined.html</loc>
|
||||
<lastmod>2025-09-11T10:23:02.116Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.967Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/api/train.html</loc>
|
||||
<lastmod>2025-09-11T10:23:01.446Z</lastmod>
|
||||
<lastmod>2025-09-12T09:59:59.306Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/multi-node.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/input_output.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.171Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.651Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/ray-integration.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/getting-started.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.169Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.649Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/optimizers.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/multi-gpu.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.171Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/dataset_preprocessing.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.168Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.648Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/torchao.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/config-reference.html</loc>
|
||||
<lastmod>2025-09-11T10:23:17.799Z</lastmod>
|
||||
<lastmod>2025-09-12T10:00:16.899Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/rlhf.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/cli.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.168Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.648Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/fsdp_qlora.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.169Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.649Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/docs/qat.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.172Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.652Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/src/axolotl/integrations/cut_cross_entropy/ACKNOWLEDGEMENTS.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.193Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.674Z</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://docs.axolotl.ai/index.html</loc>
|
||||
<lastmod>2025-09-11T10:19:40.188Z</lastmod>
|
||||
<lastmod>2025-09-12T09:55:59.669Z</lastmod>
|
||||
</url>
|
||||
</urlset>
|
||||
|
||||
Reference in New Issue
Block a user