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diff --git a/docs/backend-qwen.md b/docs/backend-qwen.md deleted file mode 100644 index 028d6f3..0000000 --- a/docs/backend-qwen.md +++ /dev/null @@ -1,67 +0,0 @@ -# Backend Option 2: Qwen3-TTS - -The easiest way is to run `python audiobook.py` → **Set up a backend… → qwen-tts** (or `python -m backends.qwen`): the TUI pip-installs `qwen-tts` into its managed venv (`envs/tts`), configures the two ports and the built-in speaker in `converter/config.py`, and prints the launch commands. You can also start the server from the hub's **Server** 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. - -Install qwen-tts with pip into your environment: - -```bash -conda activate audiobook -pip install -U qwen-tts -``` - -Run the backend with `qwen-tts-demo`. Add `--no-flash-attn` if FlashAttention isn't installed (see below). Note that the Base model and CustomVoice model run on different ports. - -## Voice clone - -```bash -qwen-tts-demo Qwen/Qwen3-TTS-12Hz-1.7B-Base --ip 127.0.0.1 --port 7861 [--no-flash-attn] -``` - -Then in another terminal: - -```bash -python audiobook.py --backend qwen --clone reference.wav -``` - -The reference `.wav` should be ~10-15 seconds (3 second minimum, 60 second maximum; ~15 seconds is ideal). Longer is **not** better. - -Whisper (`faster_whisper` or `whisper`) is used automatically to transcribe the reference audio. Without a Whisper backend it falls back to x-vector-only cloning. Override with `--transcription "What the .wav says"` or skip transcription with `--no-transcription`. - -## Custom voice (i.e. built-in voice) - -```bash -conda activate audiobook -qwen-tts-demo Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice --ip 127.0.0.1 --port 7860 [--no-flash-attn] -``` - -```bash -python audiobook.py --backend qwen -``` - -Change the voice settings in `converter/config.py`. - -## Optional: FlashAttention for qwen-tts-demo server - -FlashAttention provides a *small* speed boost on the `qwen` backend. It is **not** relevant with other backends, and switching to either of those will provide a bigger speed boost. - -`qwen-tts-demo` server tries to use FlashAttention 2 by default and requires `--no-flash-attn` without it. You have two options to install FlashAttention in your python environment: - -1. Build from source (takes absolutely forever). If you run out of memory, lower MAX_JOBS until you don't. - -```bash -conda activate audiobook -pip install ninja packaging psutil -MAX_JOBS=4 pip install --no-build-isolation flash-attn -``` - -2. pip install a prebuilt wheel matching your torch / CUDA / Python / CXX11-ABI combination: - -```bash -conda activate audiobook -python -c "import torch; print(torch.__version__, torch.version.cuda, torch._C._GLIBCXX_USE_CXX11_ABI)" -``` - -- [Official wheels](https://github.com/Dao-AILab/flash-attention/releases) - Pick `cp312` + matching `cuX` + `torchX.Y` + `cxx11abiTRUE/FALSE` -- [Third-party wheels](https://mjunya.com/flash-attention-prebuild-wheels/) |