v6.2.3
andimarafioti/faster-qwen3-ttsv6.2.3Sep 23, 2026by adamnsandle
Upgrading?
AI Summary
This release makes torchaudio an optional dependency, allowing users to choose between torchaudio, torchcodec, or no audio backend.
Key Highlights
- Torchaudio is now optional; only torch is required
- Lazy import of sequence path fixes import errors without onnxruntime
- Numpy added to onnx-cpu and onnx-gpu dependencies
Breaking Changes
- Users must now explicitly install a backend (audio, codec, or all) for audio I/O
- Changing a required dependency to optional is a breaking change for existing users
New Features
- Support for multiple audio backends (torchaudio or torchcodec)
- Lazy loading of sequence path to prevent import errors
Full Release Notes
torchaudio is now an optional dependency instead of required. Only torch is required — the model itself never used torchaudio, only the `read_audio` / `save_audio` helpers did. Users who need audio I/O must now install a backend explicitly: - `pip install silero-vad[audio]` (torchaudio) - `pip install silero-vad[codec]` (torchcodec) - `pip install silero-vad[all]` (everything) Key changes: - `read_audio` / `save_audio` now work with either torchaudio or torchcodec; with neither installed they raise an error naming the extra to install - Fixed: `import silero_vad` failed when onnxruntime was not installed — the sequence path is now imported lazily - numpy is now declared in [onnx-cpu] / [onnx-gpu] If you load audio yourself, no backend is needed at all: ```python3 from silero_vad import load_silero_vad, get_speech_timestamps model = load_silero_vad() audio = ... # 1-D float32 torch.Tensor from any source ts = get_speech_timestamps(audio, model, return_seconds=True) ```
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