Bot Updating Templated Files

.github/ISSUE_TEMPLATE/issue.bug.yml

@@ -67,10 +67,10 @@ body:
  - type: textarea
  attributes:
  description: |
- Provide a full docker log, output of "docker logs linuxserver.io"
+ Provide a full docker log, output of "docker logs emby"
  label: Container logs
  placeholder: |
- Output of `docker logs linuxserver.io`
+ Output of `docker logs emby`
  render: bash
  validations:
  required: true

.github/workflows/external_trigger_scheduler.yml

@@ -9,7 +9,7 @@ jobs:
  external-trigger-scheduler:
  runs-on: ubuntu-latest
  steps:
- - uses: actions/checkout@v3.1.0
+ - uses: actions/checkout@v4.1.1
  with:
  fetch-depth: '0'
 

.github/workflows/package_trigger.yml

@@ -7,7 +7,7 @@ jobs:
  package-trigger-master:
  runs-on: ubuntu-latest
  steps:
- - uses: actions/checkout@v3.1.0
+ - uses: actions/checkout@v4.1.1
 
  - name: Package Trigger
  if: github.ref == 'refs/heads/master'

.github/workflows/package_trigger_scheduler.yml

@@ -9,7 +9,7 @@ jobs:
  package-trigger-scheduler:
  runs-on: ubuntu-latest
  steps:
- - uses: actions/checkout@v3.1.0
+ - uses: actions/checkout@v4.1.1
  with:
  fetch-depth: '0'
 

README.md

@@ -98,7 +98,7 @@ Hardware acceleration users for Raspberry Pi V4L2 will need to mount their `/dev
 
 ### Hardware Acceleration
 
-Many desktop application will need access to a GPU to function properly and even some Desktop Environments have compisitor effects that will not function without a GPU. This is not a hard requirement and all base images will function without a video device mounted into the container.
+Many desktop applications need access to a GPU to function properly and even some Desktop Environments have compositor effects that will not function without a GPU. However this is not a hard requirement and all base images will function without a video device mounted into the container.
 
 #### Intel/ATI/AMD
 
@@ -113,9 +113,9 @@ We will automatically ensure the abc user inside of the container has the proper
 #### Nvidia
 
 Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:
-https://github.com/NVIDIA/nvidia-docker
+https://github.com/NVIDIA/nvidia-container-toolkit
 
-We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the container.
+We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-container-toolkit is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the container.
 
 #### Arm Devices