diff --git a/docs/source/qs/examples.rst b/docs/source/qs/examples.rst
index 9028c2c71..c9eb5b89f 100644
--- a/docs/source/qs/examples.rst
+++ b/docs/source/qs/examples.rst
@@ -38,7 +38,7 @@ If you plot PyTorch's result together with CVODE's result, the graph is expected
     
     Visualisation of 0D results from PyTorch and CVODE integrators 
 
-
+.. Note:: If you prefer using the PaddlePaddle framework, you can refer to examples stored in `$HOME/deepflame-dev/examples/dfLowMachFoam/paddle`.
 
 DeepFlame without DNN
 ------------------------------
diff --git a/docs/source/qs/install.rst b/docs/source/qs/install.rst
index aed71a75d..6eea02c6d 100644
--- a/docs/source/qs/install.rst
+++ b/docs/source/qs/install.rst
@@ -151,7 +151,7 @@ Finally you can build and install DeepFlame:
 
 Other Options
 -------------------------------
-DeepFlame also provides users with full GPU version and CVODE (no DNN version) options.
+DeepFlame also provides users with full GPU version, CVODE (no DNN version) and PaddlePaddle options. 
 
 **1. If you just need DeepFlame's CVODE solver without DNN model, just install LibCantera via** `conda <https://docs.conda.io/en/latest/miniconda.html#linux-installers>`_.
 
@@ -236,3 +236,7 @@ Compilition of solvers are separated. Choose the solver you want to use and then
     cmake -B build
     cd build
     make install
+
+**4. If you prefer using the PaddlePaddle framework for DNN model training and inference:**
+
+Please ensure that PaddlePaddle has been successfully installed. You can refer to the official `PaddlePaddle <https://www.paddlepaddle.org.cn/>`_ website for installation instructions.