diff --git a/ch03/01_main-chapter-code/ch03.ipynb b/ch03/01_main-chapter-code/ch03.ipynb
index 3635802..edae74f 100644
--- a/ch03/01_main-chapter-code/ch03.ipynb
+++ b/ch03/01_main-chapter-code/ch03.ipynb
@@ -204,9 +204,7 @@
    "id": "ff856c58-8382-44c7-827f-798040e6e697",
    "metadata": {},
    "source": [
-    "- By convention, the unnormalized attention weights are referred to as **\"attention scores\"** whereas the normalized attention scores, which sum to 1, are referred to as **\"attention weights\"**\n",
-    "\n",
-    "- The attention weights and context vector calculation are summarized in the figure below:"
+    "- By convention, the unnormalized attention weights are referred to as **\"attention scores\"** whereas the normalized attention scores, which sum to 1, are referred to as **\"attention weights\"**\n"
    ]
   },
   {
@@ -2002,7 +2000,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/ch05/03_bonus_pretraining_on_gutenberg/README.md b/ch05/03_bonus_pretraining_on_gutenberg/README.md
index ba82c6f..36f9c96 100644
--- a/ch05/03_bonus_pretraining_on_gutenberg/README.md
+++ b/ch05/03_bonus_pretraining_on_gutenberg/README.md
@@ -7,7 +7,7 @@ As the Project Gutenberg website states, "the vast majority of Project Gutenberg
 Please read the [Project Gutenberg Permissions, Licensing and other Common Requests](https://www.gutenberg.org/policy/permission.html) page for more information about using the resources provided by Project Gutenberg. 
 
  
-## How to use this code
+## How to Use This Code
 
  
 
@@ -17,7 +17,11 @@ In this section, we download books from Project Gutenberg using code from the [`
 
 As of this writing, this will require approximately 50 GB of disk space, but it may be more depending on how much Project Gutenberg grew since then.
 
-Follow these steps to download the dataset:
+ 
+#### Download instructions for Linux and macOS users
+
+
+Linux and macOS users can follow these steps to download the dataset (if you are a Windows user, please see the note below):
 
 
 1. `git clone https://github.com/pgcorpus/gutenberg.git`
@@ -31,8 +35,26 @@ Follow these steps to download the dataset:
 5. `cd ..`
 
  
+#### Special instructions for Windows users
+
+The [`pgcorpus/gutenberg`](https://github.com/pgcorpus/gutenberg) code is compatible with both Linux and macOS. However, Windows users would have to make small adjustments, such as adding `shell=True` to the `subprocess` calls and replacing `rsync`. 
+
+Alternatively, an easier way to run this code on Windows is by using the "Windows Subsystem for Linux" (WSL) feature, which allows users to run a Linux environment using Ubuntu in Windows. For more information, please read [Microsoft's official installation instruction](https://learn.microsoft.com/en-us/windows/wsl/install) and [tutorial](https://learn.microsoft.com/en-us/training/modules/wsl-introduction/). 
+
+When using WSL, please make sure you have Python 3 installed (check via `python3 --version`, or install it for instance with `sudo apt-get install -y python3.10` for Python 3.10) and install following packages there:
+
+```bash
+sudo apt-get update && \
+sudo apt-get upgrade -y && \
+sudo apt-get install -y python3-pip && \
+sudo apt-get install -y python-is-python3 && \
+sudo apt-get install -y rsync && \
+```
+
 > [!NOTE]
-> The [`pgcorpus/gutenberg`](https://github.com/pgcorpus/gutenberg) code is compatible with both Linux and macOS. However, Windows users would have to make small adjustments, such as adding `shell=True` to the `subprocess` calls and replacing `rsync`. Alternatively, an easier way to run this code on Windows is by using the "Windows Subsystem for Linux" feature, which allows users to run a Linux environment in Windows. For more information, please read [Microsoft's official installation instruction](https://learn.microsoft.com/en-us/windows/wsl/install) and [tutorial](https://learn.microsoft.com/en-us/training/modules/wsl-introduction/).
+> Instructions about how to set up Python and installing packages can be found in  [Appendix A: Optional Python Setup Preferences](../../appendix-A/01_optional-python-setup-preferences/README.md) and [Appendix A: Installing Python Libraries](../../appendix-A/02_installing-python-libraries/README.md).
+>
+> Optionally, a Docker image running Ubuntu is provided with this repository. When having cloned the [`pgcorpus/gutenberg`](https://github.com/pgcorpus/gutenberg) GitHub repository, copy the *.devcontainer* folder of this `LLMs-from-scratch` repository and paste it to the locally cloned `gutenberg` repository. Instructions about how to run a container with the provided Docker image can be found in [Appendix A: Optional Docker Environment](../../appendix-A/04_optional-docker-environment/README.md).
 
  
 ### 2) Prepare the dataset