From d97e9151637be3c80e3f8ac32ade1ea8191deefe Mon Sep 17 00:00:00 2001
From: William Zhang <108840645+WilliamZhang20@users.noreply.github.com>
Date: Wed, 10 Dec 2025 19:37:32 -0500
Subject: [PATCH] update hyperlink

---
 docs/source/tutorials_source/pt2e_quant_qat.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/tutorials_source/pt2e_quant_qat.rst b/docs/source/tutorials_source/pt2e_quant_qat.rst
index d8eb013d70..87422b3e28 100644
--- a/docs/source/tutorials_source/pt2e_quant_qat.rst
+++ b/docs/source/tutorials_source/pt2e_quant_qat.rst
@@ -5,7 +5,7 @@ PyTorch 2 Export Quantization-Aware Training (QAT)
 This tutorial shows how to perform quantization-aware training (QAT) in
 graph mode based on `torch.export.export <https://pytorch.org/docs/main/export.html>`_.
 For more details about PyTorch 2 Export Quantization in general, refer
-to the `post training quantization tutorial <https://docs.pytorch.org/ao/stable/tutorial_source/pt2e_quant_ptq.html>`_
+to the `post training quantization tutorial <https://docs.pytorch.org/ao/stable/tutorials_source/pt2e_quant_ptq.html>`_
 
 The PyTorch 2 Export QAT flow looks like the following—it is similar
 to the post training quantization (PTQ) flow for the most part: