feat: settings for ports in TUI

1 files changed, 1 insertions, 1 deletions

diff --git a/app/docs/backend-faster.md b/app/docs/backend-faster.md
index 4d193b7..1f22d99 100644
--- a/app/docs/backend-faster.md
+++ b/app/docs/backend-faster.md
@@ -2,7 +2,7 @@
 
 `--backend faster` talks to the OpenAI-compatible server from [faster-qwen3-tts](https://github.com/andimarafioti/faster-qwen3-tts), which uses CUDA graph capture for roughly 5-10x faster inference with the same models. **It requires an NVIDIA GPU**.
 
-The easiest way is to run `python audiobook.py` → **Set up a backend… → faster-qwen3-tts** (or `python app/backends/faster.py path/to/clone/wavs`): the TUI pip-installs `faster-qwen3-tts[demo]` into its managed venv (`app/envs/tts`), clones the repo, transcribes the `.wav` files with `whisper`, and writes `voices.json` for you. You can also start the server from the hub's **Server** menu, or let a conversion start it automatically.
+The easiest way is to run `python audiobook.py` → **Set up a backend… → faster-qwen3-tts** (or `python app/backends/faster.py path/to/clone/wavs`): the TUI pip-installs `faster-qwen3-tts[demo]` into its managed venv (`app/envs/tts`), clones the repo, transcribes the `.wav` files with `whisper`, and writes `voices.json` for you. You can also start the server from the hub's **Start/Stop Backend Servers** menu, or let a conversion start it automatically.
 
 If you prefer to install the backend yourself (in your own environment, not the managed venv), the manual steps are below. Either way the hub detects a running server by its port, so a manually-installed backend works once its server is up.