update 2.1.30 llm.html (#2876)

intel · May 13, 2024 · d85c47f · d85c47f
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diff --git a/xpu/2.1.30+xpu/_sources/tutorials/llm.rst.txt b/xpu/2.1.30+xpu/_sources/tutorials/llm.rst.txt
@@ -48,7 +48,7 @@ Optimized Models
 
 *Note*: The above verified models (including other models in the same model family, like "codellama/CodeLlama-7b-hf" from LLAMA family) are well supported with all optimizations like indirect access KV cache, fused ROPE, and prepacked TPP Linear (fp16). For other LLMs families, we are working in progress to cover those optimizations, which will expand the model list above.
 
-Check `LLM best known practice <https://github.com/intel/intel-extension-for-pytorch/tree/v2.1.30%2Bxpu/examples/gpu/inference/python/llm>`_ for instructions to install/setup environment and example scripts..
+Check `LLM best known practice <https://github.com/intel/intel-extension-for-pytorch/tree/release/xpu/2.1.30/examples/gpu/inference/python/llm>`_ for instructions to install/setup environment and example scripts..
 
 Optimization Methodologies
 --------------------------

diff --git a/xpu/2.1.30+xpu/tutorials/llm.html b/xpu/2.1.30+xpu/tutorials/llm.html
@@ -163,7 +163,7 @@ <h2>Optimized Models<a class="headerlink" href="#optimized-models" title="Permal
 </tbody>
 </table>
 <p><em>Note</em>: The above verified models (including other models in the same model family, like “codellama/CodeLlama-7b-hf” from LLAMA family) are well supported with all optimizations like indirect access KV cache, fused ROPE, and prepacked TPP Linear (fp16). For other LLMs families, we are working in progress to cover those optimizations, which will expand the model list above.</p>
-<p>Check <a class="reference external" href="https://github.com/intel/intel-extension-for-pytorch/tree/v2.1.30%2Bxpu/examples/gpu/inference/python/llm">LLM best known practice</a> for instructions to install/setup environment and example scripts..</p>
+<p>Check <a class="reference external" href="https://github.com/intel/intel-extension-for-pytorch/tree/release/xpu/2.1.30/examples/gpu/inference/python/llm">LLM best known practice</a> for instructions to install/setup environment and example scripts..</p>
 </section>
 <section id="optimization-methodologies">
 <h2>Optimization Methodologies<a class="headerlink" href="#optimization-methodologies" title="Permalink to this heading"></a></h2>
@@ -260,4 +260,4 @@ <h2>Weight Only Quantization INT4<a class="headerlink" href="#weight-only-quanti
   </script> 
 
 </body>
-</html>
+</html>