chore: Regenerate all playbooks

nvidia/station-brev/README.md

@@ -52,21 +52,18 @@ You will also need the following:
 
 ## Step 1. Log in to Brev
 
-Go to the [Brev UI](https://brev.nvidia.com), log in, and confirm you’re in the correct org (by clicking the org button on the top right-hand side of the page). Once logged in, go to the [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute) section under the "GPU" tab in the main navigation.
+Go to the [Brev UI](https://brev.nvidia.com), log in, and confirm you’re in the correct org (by clicking the org button on the top right hand side of the page). Once logged in, go to the [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute) section under the "GPU" tab in the main navigation.
 
 Click the “Register Compute” button and follow the instructions in the pop-up window.
 
-## Step 2. Complete Pop-up Instructions
+## Step 2. Complete Popup Instructions
 
 * Install the Brev CLI
 * Configure your compute
     * Add a name for compute
-    * To configure SSH, ensure the “Enable SSH access” toggle is on
+    * To configure ssh, ensure the “Enable SSH access” toggle is on
 * Run the registration command
 
-> [!IMPORTANT]
-> Run the Brev CLI install command **without `sudo`**. Prefixing the installer with `sudo` writes the `brev` binary into root's home directory, which is not on your user shell's `PATH` — the next command will fail with `brev: command not found`. Copy the install command from the pop-up and run it as your normal user.
-
 ## Step 3. Follow Registration Flow
 
 In the CLI, you’ll be walked through registration. Go through the flow until registration is complete.
@@ -83,14 +80,10 @@ Your DGX Station is now integrated into Brev as a secure, remotely accessible GP
 
 Now that your hardware is connected, you can:
 
-* **Access your machine from anywhere:** Open the [Brev UI](https://brev.nvidia.com) and launch a session from [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute).
+* **Share Access Anywhere:** Access your machine from anywhere and share access with others through the Brev UI by:
-* **Share access with others:** Invite teammates to your DGX Station from the Brev UI:
+    * Adding the user to your [Team](https://brev.nvidia.com/org/team)
-    * Go to the [Brev UI](https://brev.nvidia.com) and open [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute).
+    * Navigating to your instance in the [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute) section
-    * Find your DGX Station in the list and open the row's three-dot (⋯) menu.
+    * In **SSH Access** section of the instance, search for the user you wish to add and click **Modify Access** to enable access
-    * Select **Share Access**.
-    * Enter the email address of the person you want to share with.
-    * Choose their role / permission level.
-    * Confirm to send the invitation.
 
 ## Step 6. Cleanup
 
@@ -105,7 +98,7 @@ brev deregister
 In the UI:
 * Go to the [Brev UI](https://brev.nvidia.com)
 * Navigate to the section listing “GPU Environments” and look under “Registered Compute”
-* Click the “Remove” menu item on the device you wish to delete from Brev.
+* Click the “Remove” menu item on the DGX Station you wish to delete from Brev.
 * Confirm your selection.
 
 ## Troubleshooting

nvidia/station-brev/endpoint-test.yaml

@@ -82,21 +82,18 @@ spec:
       content: |
         # Step 1. Log in to Brev
         
-        Go to the [Brev UI](https://brev.nvidia.com), log in, and confirm you’re in the correct org (by clicking the org button on the top right-hand side of the page). Once logged in, go to the [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute) section under the "GPU" tab in the main navigation.
+        Go to the [Brev UI](https://brev.nvidia.com), log in, and confirm you’re in the correct org (by clicking the org button on the top right hand side of the page). Once logged in, go to the [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute) section under the "GPU" tab in the main navigation.
         
         Click the “Register Compute” button and follow the instructions in the pop-up window.
         
-        # Step 2. Complete Pop-up Instructions
+        # Step 2. Complete Popup Instructions
         
         * Install the Brev CLI
         * Configure your compute
             * Add a name for compute
-            * To configure SSH, ensure the “Enable SSH access” toggle is on
+            * To configure ssh, ensure the “Enable SSH access” toggle is on
         * Run the registration command
         
-        > [!IMPORTANT]
-        > Run the Brev CLI install command **without `sudo`**. Prefixing the installer with `sudo` writes the `brev` binary into root's home directory, which is not on your user shell's `PATH` — the next command will fail with `brev: command not found`. Copy the install command from the pop-up and run it as your normal user.
-        
         # Step 3. Follow Registration Flow
         
         In the CLI, you’ll be walked through registration. Go through the flow until registration is complete.
@@ -113,14 +110,10 @@ spec:
         
         Now that your hardware is connected, you can:
         
-        * **Access your machine from anywhere:** Open the [Brev UI](https://brev.nvidia.com) and launch a session from [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute).
+        * **Share Access Anywhere:** Access your machine from anywhere and share access with others through the Brev UI by:
-        * **Share access with others:** Invite teammates to your DGX Station from the Brev UI:
+            * Adding the user to your [Team](https://brev.nvidia.com/org/team)
-            * Go to the [Brev UI](https://brev.nvidia.com) and open [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute).
+            * Navigating to your instance in the [Registered Compute](https://brev.nvidia.com/org/environments?tab=registered-compute) section
-            * Find your DGX Station in the list and open the row's three-dot (⋯) menu.
+            * In **SSH Access** section of the instance, search for the user you wish to add and click **Modify Access** to enable access
-            * Select **Share Access**.
-            * Enter the email address of the person you want to share with.
-            * Choose their role / permission level.
-            * Confirm to send the invitation.
         
         # Step 6. Cleanup
         
@@ -135,7 +128,7 @@ spec:
         In the UI:
         * Go to the [Brev UI](https://brev.nvidia.com)
         * Navigate to the section listing “GPU Environments” and look under “Registered Compute”
-        * Click the “Remove” menu item on the device you wish to delete from Brev.
+        * Click the “Remove” menu item on the DGX Station you wish to delete from Brev.
         * Confirm your selection.
         
       

nvidia/station-nanochat/endpoint-production.yaml

@@ -107,7 +107,7 @@ spec:
         
         # Time & risk
         
-        - **Estimated time:** ~30 minutes for setup. Full d24 training takes on the order of 16+ hours on a single GB300 Ultra.
+        - **Estimated time:** ~30 minutes for setup. Full d24 training takes on the order of 12+ hours on a single GB300 Ultra.
         - **Risk level:** Medium
           - Large downloads (FineWeb) can be slow; ensure stable network and disk space.
           - API keys (W&B, HF) must be set or `launch.sh` will exit immediately.
@@ -184,7 +184,7 @@ spec:
         3. **SFT** — downloads synthetic identity conversations, fine-tunes for chat
         4. **Report generation** — produces `report.md` with metrics and samples
         
-        Training on a single GB300 Ultra takes on the order of 16+ hours for the full d24 run.
+        Training on a single GB300 Ultra takes on the order of 12+ hours for the full d24 run.
         
         # Step 4. Monitor training