1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
|
# Backend Option 3: faster-qwen-tts
`--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` → **Configure backends… → Install 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 (faster-whisper, installed when wheels exist for your platform — otherwise you type the transcripts), and writes `voices.json` for you — all on one options screen (voices directory, language, whisper model, and what to re-transcribe on a modify run). The server port is not asked: it lives in `FASTER_API_URL` (edit it in **Settings**). 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. To use a server on another machine, set `FASTER_REMOTE_URL` in `app/converter/config.py` to its `host:port` (default `127.0.0.1:8000`) — the hub probes it and offers a `faster-qwen3-tts [remote]` entry — or pass `--api-url` on the CLI.
Install into your environment (the same one used for qwen-tts is fine):
```bash
python -m venv audiobook
source audiobook/bin/activate
pip install -U qwen-tts
pip install "faster-qwen3-tts[demo]"
```
**This backend always uses voice cloning**. The reference voice and language are configured on the **server**, not through the converter. The server does not transcribe reference audio itself, so do it manually or use the `backends.faster` setup wizard (see below).
The pip package does not include the server script, so clone the repository (the `backends.faster` wizard does this for you into `./faster-qwen3-tts`):
```bash
git clone https://github.com/andimarafioti/faster-qwen3-tts
cd faster-qwen3-tts
```
Create a `voices.json` mapping names to reference configurations (.wav to clone, transcript, language). The TUI setup writes this for you; manually it looks like:
```json
{
"default": {"ref_audio": "voice1.wav", "ref_text": "Transcript of voice 1.", "language": "English"},
"obama": {"ref_audio": "voice2.wav", "ref_text": "Transcript of voice 2.", "language": "English"}
}
```
Run the server
```bash
python examples/openai_server.py --voices voices.json --port 8000
```
Then from another terminal, run audiobook.py with `--backend faster`
```bash
python audiobook.py --backend faster [--voice NAME]
```
|
