announcements embed

Author: s-sajid-ali

docs/hpc/01_getting_started/01_intro.mdx

@@ -4,6 +4,6 @@ Welcome to the Torch HPC documentation! If you do not have an HPC account, pleas
 
 If you are an active user, you can proceed to one of the categories on the left.
 
-## Annoucements
+## Announcements
 
 <iframe src="https://docs.google.com/presentation/d/16ngaLYw236Zr1fI8oPirK6Qz6EEDnpdhtRiJ3sCgEz8/present#slide=id.g388ef242c2c_0_0" frameborder="0" width="960" height="569" allowfullscreen="true" mozallowfullscreen="true" webkitallowfullscreen="true"></iframe> 

docs/hpc/03_storage/08_transferring_cloud_storage_data_with_rclone.md

@@ -344,7 +344,7 @@ Please enter 'q' and we're done with configuration.
 
 ### Step 4: Transfer
 :::warning
-Please be sure to perform data transters on a data transfer node (DTN).  It can degrade performance for other users to perform transfers on other types of nodes.  For more information please see [Data Transfers](./03_data_transfers.md)
+Please be sure to perform data transfers on a data transfer node (DTN).  It can degrade performance for other users to perform transfers on other types of nodes.  For more information please see [Data Transfers](./03_data_transfers.md)
 :::
 
 Sample commands:

docs/hpc/06_tools_and_software/01_intro.md

@@ -3,7 +3,7 @@
 We encourage you to setup your own computational environment on Torch and to assist you in doing so, we allow you to run [Apptainer](../07_containers/01_intro.md) (formerly known as Singularity) containers, we manage licensed software suites and offer extensive documentation, training and support.
 
 :::tip
-We stongly advise that you setup your own computational enviromments via Apptainer containers and overlay files. Detailed documentation is available in the [containers section](../07_containers/01_intro.md).
+We strongly advise that you setup your own computational enviromments via Apptainer containers and overlay files. Detailed documentation is available in the [containers section](../07_containers/01_intro.md).
 :::
 
 ## Package Management for R, Python, & Julia, and Conda in general