diff --git a/docs/source/documents/usage/installation.rst b/docs/source/documents/usage/installation.rst
index 06e93142..7cf6eeb3 100644
--- a/docs/source/documents/usage/installation.rst
+++ b/docs/source/documents/usage/installation.rst
@@ -35,12 +35,18 @@ Install via PyPI
 
 .. tabs::
 
-    .. group-tab:: PyTorch
+    .. group-tab:: No DL toolbox
 
         .. code-block:: bash
 
             pip install xuance
 
+    .. group-tab:: PyTorch
+
+        .. code-block:: bash
+
+            pip install xuance[torch]
+
     .. group-tab:: TensorFlow
 
         .. code-block:: bash
@@ -109,12 +115,18 @@ Alternatively, you can install XuanCe from its GitHub repository.
 
 .. tabs::
 
-    .. group-tab:: PyTorch
+    .. group-tab:: No DL toolbox
 
         .. code-block:: bash
 
             pip install -e .
 
+    .. group-tab:: PyTorch
+
+        .. code-block:: bash
+
+            pip install -e .[torch]
+
     .. group-tab:: TensorFlow
 
         .. code-block:: bash
diff --git a/setup.py b/setup.py
index 460bb28d..97c2cc96 100644
--- a/setup.py
+++ b/setup.py
@@ -14,7 +14,7 @@
                 "environment/magent2/libmagent.dylib"  # for magent2 environment on MacOS (for Intel CPU)
             ]
     },
-    version="1.1.0",
+    version="1.1.1",
     description='XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library.',
     long_description='XuanCe is an open-source ensemble of Deep Reinforcement Learning (DRL) algorithm implementations. We call it as Xuan-Ce (玄策) in Chinese. "Xuan (玄)" means incredible and magic box, "Ce (策)" means policy. DRL algorithms are sensitive to hyper-parameters tuning, varying in performance with different tricks, and suffering from unstable training processes, therefore, sometimes DRL algorithms seems elusive and "Xuan". This project gives a thorough, high-quality and easy-to-understand implementation of DRL algorithms, and hope this implementation can give a hint on the magics of reinforcement learning. We expect it to be compatible with multiple deep learning toolboxes( PyTorch, TensorFlow, and MindSpore), and hope it can really become a zoo full of DRL algorithms.',
     author='Wenzhang Liu, et al.',