diff --git a/nvidia/vllm/README.md b/nvidia/vllm/README.md
index cfe3d6a..2b3ee6a 100644
--- a/nvidia/vllm/README.md
+++ b/nvidia/vllm/README.md
@@ -164,13 +164,6 @@ docker rm $(docker ps -aq --filter ancestor=nvcr.io/nvidia/vllm:${LATEST_VLLM_VE
 docker rmi nvcr.io/nvidia/vllm
 ```
 
-
-To remove CUDA 12.9:
-
-```bash
-sudo /usr/local/cuda-12.9/bin/cuda-uninstaller
-```
-
 ## Step 5. Next steps
 
 - **Production deployment:** Configure vLLM with your specific model requirements
diff --git a/nvidia/vscode/README.md b/nvidia/vscode/README.md
index 353eada..20b1289 100644
--- a/nvidia/vscode/README.md
+++ b/nvidia/vscode/README.md
@@ -174,7 +174,7 @@ rm -rf ~/.vscode
 
 ## Step 1. Install and configure NVIDIA Sync
 
-Follow the [NVIDIA Sync setup guide](/spark/connect-to-your-spark/sync) to:
+Follow the [NVIDIA Sync setup guide](https://build.nvidia.com/spark/connect-to-your-spark/sync) to:
 - Install NVIDIA Sync for your operating system
 - Configure which development tools you want to use (VS Code, Cursor, Terminal, etc.)
 - Add your DGX Spark device by providing its hostname/IP and credentials