diff --git a/README.md b/README.md
index 9bf414c..d4d622f 100644
--- a/README.md
+++ b/README.md
@@ -216,11 +216,17 @@ DeepSpeed Version 11.2 with CUDA 12.1 - Installation Instructions:
 
 1. Download the 11.2 release of [DeepSpeed](https://github.com/microsoft/DeepSpeed/releases/tag/v0.11.2) extract it to a folder. 
 2. Install Visual C++ build tools, such as [VS2019 C++ x64/x86](https://learn.microsoft.com/en-us/visualstudio/releases/2019/redistribution#vs2019-download) build tools.
-3. Download and install the [Nvidia Cuda Toolkit 12.1](https://developer.nvidia.com/cuda-12-1-0-download-archive)
+3. Download and install the [Nvidia Cuda Toolkit 11.8 or 12.1](https://developer.nvidia.com/cuda-toolkit-archive))
 4. Edit your Windows environment variables to ensure that CUDA_HOME and CUDA_PATH are set to your Nvidia Cuda Toolkit path. (The folder above the bin folder that nvcc.exe is installed in). Examples are:<br>
+
 ```set CUDA_HOME=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1```<br>
 ```set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1```<br>
 
+Or
+
+```set CUDA_HOME=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8```<br>
+```set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8```<br>
+
 5. OPTIONAL If you do not have an python environment already created, you can install [Miniconda](https://docs.conda.io/projects/miniconda/en/latest/miniconda-install.html), then at a command prompt, create and activate your environment with:<br>
 ```conda create -n pythonenv python=3.11```<br>
 ```activate pythonenv```<br>
@@ -230,15 +236,19 @@ DeepSpeed Version 11.2 with CUDA 12.1 - Installation Instructions:
 ```activate pythonenv``` (activate your python environment)<br>
 ```conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia```
 
-8. In your python environment check that your CUDA_HOME and CUDA_PATH are still pointing to the correct location.<br>
+or
+
+```conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 -c pytorch -c nvidia```
+
+9. In your python environment check that your CUDA_HOME and CUDA_PATH are still pointing to the correct location.<br>
 ```set``` (to list and check the windows environment variables. Refer to step 4 if not)
 
-9. Navigate to your deepspeed folder in the Command Prompt:<br>
+10. Navigate to your deepspeed folder in the Command Prompt:<br>
 ```cd c:\deepspeed``` (wherever you extracted it to)
 
-10. Modify the following files:<br>
+11. Modify the following files:<br>
 
-**(These modified files are included in the git-pull of AllTalk, but if you want to modify them yourself, please follow the below)**
+**(These modified files are included in the git-pull of AllTalk, in the DeepSpeed Windows folder but if you want to modify them yourself, please follow the below)**
 
 deepspeed-0.11.2/build_win.bat** - at the top of the file, add:<br>
  ```set DS_BUILD_EVOFORMER_ATTN=0```
@@ -297,9 +307,9 @@ def get_shm_size():
 ```
 
 11. While still in your command line with python environment enabled run:<br>
-```build_win.bat```
+```build_win.bat``` and wait 10-20 minutes.
 
-12. Now cd dist to go into your dist folder and you can now pip install deepspeed-YOURFILENAME.whl (or whatever your WHL file is called).
+12. Now `cd dist` to go into your dist folder and you can now `pip install deepspeed-YOURFILENAME.whl` (or whatever your WHL file is called).
 
 ### 🔴 Future to-do list
 - Complete & document the new/full standalone mode API.