diff --git a/docs/install.rst b/docs/install.rst
index 2790cc1..fb59c8e 100644
--- a/docs/install.rst
+++ b/docs/install.rst
@@ -48,6 +48,6 @@ the most recent version of CUDA, Docker, and nvidia-docker.
 After performing the above setup, you can pull the PyProf container
 using the following command::
 
-  docker pull nvcr.io/nvidia/pytorch:20.07-py3
+  docker pull nvcr.io/nvidia/pytorch:20.11-py3
 
-Replace *20.07* with the version of PyTorch container that you want to pull.
+Replace *20.11* with the version of PyTorch container that you want to pull.
diff --git a/docs/quickstart.rst b/docs/quickstart.rst
index 6567248..26fcf13 100644
--- a/docs/quickstart.rst
+++ b/docs/quickstart.rst
@@ -39,7 +39,7 @@ Prerequisites
   drop down button. After cloning the repo be sure to select the r<xx.yy> 
   release branch that corresponds to the version of PyProf want to use::
 
-  $ git checkout r20.07
+  $ git checkout r20.11
 
 * If you are starting with a pre-built NGC container, you will need to install 
   Docker and nvidia-docker. For DGX users, see `Preparing to use NVIDIA Containers
@@ -75,8 +75,8 @@ the GitHub repo and checkout the release version of the branch that
 you want to build (or the master branch if you want to build the
 under-development version)::
 
-  $ git checkout r20.07
-
+  $ git checkout r20.11
+  
 Then use docker to build::
 
   $ docker build --pull -t pyprof .