From 256d474bda61f9419e5707a13554c4957d4f57de Mon Sep 17 00:00:00 2001
From: Quarto GHA Workflow Runner <quarto-github-actions-publish@example.com>
Date: Wed, 16 Apr 2025 05:19:29 +0000
Subject: [PATCH] Built site for gh-pages

---
 .nojekyll                     |   2 +-
 docs/custom_integrations.html |   2 +-
 search.json                   |   2 +-
 sitemap.xml                   | 340 +++++++++++++++++-----------------
 4 files changed, 173 insertions(+), 173 deletions(-)

diff --git a/.nojekyll b/.nojekyll
index 709e12af4..41b744d64 100644
--- a/.nojekyll
+++ b/.nojekyll
@@ -1 +1 @@
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+39794ace
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diff --git a/docs/custom_integrations.html b/docs/custom_integrations.html
index a99c34419..1a1951e98 100644
--- a/docs/custom_integrations.html
+++ b/docs/custom_integrations.html
@@ -521,7 +521,7 @@ pre > code.sourceCode > span > a:first-child::before { text-decoration: underlin
 <p>Run the following command to install <code>cut_cross_entropy[transformers]</code> if you don’t have it already.</p>
 <div class="sourceCode" id="cb1"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="ex">python</span> scripts/cutcrossentropy_install.py <span class="kw">|</span> <span class="fu">sh</span></span>
 <span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> uninstall <span class="at">-y</span> cut-cross-entropy <span class="kw">&amp;&amp;</span> <span class="ex">pip3</span> install <span class="st">"cut-cross-entropy[transformers] @ git+https://github.com/apple/ml-cross-entropy.git@24fbe4b5dab9a6c250a014573613c1890190536c"</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> uninstall <span class="at">-y</span> cut-cross-entropy <span class="kw">&amp;&amp;</span> <span class="ex">pip3</span> install <span class="st">"cut-cross-entropy[transformers] @ git+https://github.com/apple/ml-cross-entropy.git@bad6f7b49c75fdec69471abb71b4cddd0f0c6438"</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </section>
 <section id="usage" class="level3">
 <h3 class="anchored" data-anchor-id="usage">Usage</h3>
diff --git a/search.json b/search.json
index 4c79d86b1..724a878dc 100644
--- a/search.json
+++ b/search.json
@@ -3033,7 +3033,7 @@
     "href": "docs/custom_integrations.html#cut-cross-entropy",
     "title": "Custom Integrations",
     "section": "Cut Cross Entropy",
-    "text": "Cut Cross Entropy\nCut Cross Entropy (CCE) reduces VRAM usage through optimization on the cross-entropy operation during loss calculation.\nSee https://github.com/apple/ml-cross-entropy\n\nRequirements\n\nPyTorch 2.4.0 or higher\n\n\n\nInstallation\nRun the following command to install cut_cross_entropy[transformers] if you don’t have it already.\npython scripts/cutcrossentropy_install.py | sh\n\npip3 uninstall -y cut-cross-entropy && pip3 install \"cut-cross-entropy[transformers] @ git+https://github.com/apple/ml-cross-entropy.git@24fbe4b5dab9a6c250a014573613c1890190536c\"\n\n\nUsage\nplugins:\n  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin\n\ncut_cross_entropy: true\n\n\nSupported Models\n\nllama\nllama4_text\nllama4\nmllama\nphi3\ngemma\ngemma2\ngemma3\ngemma3_text\nmistral\nmistral3\nqwen2\ncohere\ncohere2\n\n\n\nCitation\n@article{wijmans2024cut,\n  author       = {Erik Wijmans and\n                  Brody Huval and\n                  Alexander Hertzberg and\n                  Vladlen Koltun and\n                  Philipp Kr\\\"ahenb\\\"uhl},\n  title        = {Cut Your Losses in Large-Vocabulary Language Models},\n  journal      = {arXiv},\n  year         = {2024},\n  url          = {https://arxiv.org/abs/2411.09009},\n}\nPlease see reference here",
+    "text": "Cut Cross Entropy\nCut Cross Entropy (CCE) reduces VRAM usage through optimization on the cross-entropy operation during loss calculation.\nSee https://github.com/apple/ml-cross-entropy\n\nRequirements\n\nPyTorch 2.4.0 or higher\n\n\n\nInstallation\nRun the following command to install cut_cross_entropy[transformers] if you don’t have it already.\npython scripts/cutcrossentropy_install.py | sh\n\npip3 uninstall -y cut-cross-entropy && pip3 install \"cut-cross-entropy[transformers] @ git+https://github.com/apple/ml-cross-entropy.git@bad6f7b49c75fdec69471abb71b4cddd0f0c6438\"\n\n\nUsage\nplugins:\n  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin\n\ncut_cross_entropy: true\n\n\nSupported Models\n\nllama\nllama4_text\nllama4\nmllama\nphi3\ngemma\ngemma2\ngemma3\ngemma3_text\nmistral\nmistral3\nqwen2\ncohere\ncohere2\n\n\n\nCitation\n@article{wijmans2024cut,\n  author       = {Erik Wijmans and\n                  Brody Huval and\n                  Alexander Hertzberg and\n                  Vladlen Koltun and\n                  Philipp Kr\\\"ahenb\\\"uhl},\n  title        = {Cut Your Losses in Large-Vocabulary Language Models},\n  journal      = {arXiv},\n  year         = {2024},\n  url          = {https://arxiv.org/abs/2411.09009},\n}\nPlease see reference here",
     "crumbs": [
       "Advanced Features",
       "Custom Integrations"
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