Add documentation for hosting the ML container on a different machine

docs/docs/install/docker-compose.md

@@ -154,6 +154,40 @@ IMMICH_MACHINE_LEARNING_URL=http://immich-machine-learning:3003
 - Consider changing `DB_PASSWORD` to something randomly generated
 - Consider changing `TYPESENSE_API_KEY` to something randomly generated
 
+<details>
+<summary>Hosting the machine-learning service on a different system</summary>
+
+To alleviate [performance issues on low-memory systems](/docs/FAQ.md#why-is-immich-slow-on-low-memory-systems-like-the-raspberry-pi) like the Raspberry Pi, you may also host Immich's machine-learning container on a more powerful system (e.g. your laptop or desktop computer):
+
+- Set `IMMICH_MACHINE_LEARNING_URL` to point to the designated ML system, e.g. `http://workstation:3003`
+- Copy your `.env` file and the following `docker-compose.yml` to the ML system:
+
+```yaml
+version: "3.8"
+
+services:
+
+  immich-machine-learning:
+    container_name: immich_machine_learning
+    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
+    volumes:
+      - model-cache:/cache
+    env_file:
+      - .env
+    restart: always
+    ports:
+      - 3003:3003
+
+volumes:
+  model-cache:
+```
+
+- Start the ML container by running `docker-compose up -d` or `docker compose up -d` (depending on your `docker-compose` version).
+
+</details>
+
+
+
 ### Step 3 - Start the containers
 
 From the directory you created in Step 1, (which should now contain your customized `docker-compose.yml` and `.env` files) run `docker-compose up -d`.