diff --git a/docs/hw-transcoding.md b/docs/hw-transcoding.md
index f020ccbf0..9a88f4856 100644
--- a/docs/hw-transcoding.md
+++ b/docs/hw-transcoding.md
@@ -26,11 +26,11 @@ NVIDIA GPUs support hardware transcoding using NVENC.
 
 ## External Transcoder
 
-!!! success "Recommmended Configuration"
+!!! success "Recommended Configuration"
 
     The easiest and recommended way to use hardware transcoding in a docker environment is to use an external transcoder.
     This setup utilizes a separate docker container that contains the hardware drivers and ffmpeg.
-    If you cannot do this, other installation methods are also possible (see below).
+    If you cannot do this, other installation methods are also possible.
 
 [go-vod](https://github.com/pulsejet/memories/tree/master/go-vod), the transcoder of Memories, comes with a pre-built Docker image based on `linuxserver/ffmpeg`. The docker image connects to your Nextcloud instance and pulls the go-vod binary on startup. To set up an external transcoder, follow these steps.
 
diff --git a/docs/install.md b/docs/install.md
index eff855bcc..d91008e6d 100644
--- a/docs/install.md
+++ b/docs/install.md
@@ -14,7 +14,7 @@ For the best experience, we recommend to use the latest stable version of Nextcl
 For easy setup and maintenance, you can use the community Nextcloud Docker image, and add extra dependencies using a custom Dockerfile.
 Another option is to use [Nextcloud AIO](https://github.com/nextcloud/all-in-one#how-to-use-this), in which case most dependencies are already installed.
 
-!!! success "Recommmended Configuration"
+!!! success "Recommended Configuration"
 
     If you plan to use hardware transcoding, using **Docker Compose** or **Nextcloud AIO** is recommended.