metadata
license: apache-2.0
language:
- zh
- en
library_name: gguf
tags:
- voice-activity-detection
- vad
- fsmn
- funasr
- llama.cpp
- ggml
- cpu
- on-device
pipeline_tag: voice-activity-detection
FSMN-VAD · GGUF (FunASR llama.cpp runtime)
GGUF build of FunASR's FSMN-VAD for the zero-Python, CPU/edge FunASR llama.cpp runtime. Native ggml voice-activity detection: segment long audio entirely in C++, no Python at runtime.
Get it running (no Python, no build)
These are GGUF weights for the FunASR llama.cpp runtime — a whisper.cpp-style, single self-contained binary for CPU / edge. Grab a prebuilt binary, then fetch this model and run:
- Prebuilt binaries (Linux / macOS / Windows) → GitHub Releases (tag
runtime-llamacpp-v*) - One-page quickstart & benchmarks → funasr.com/llama-cpp
bash download-funasr-model.sh fsmn-vad ./gguf
# fsmn-vad is the VAD used by the ASR runtimes via --vad (see the SenseVoice / Paraformer / Fun-ASR-Nano GGUF repos)
Files
| file | size | notes |
|---|---|---|
fsmn-vad.gguf |
1.7 MB | FSMN encoder + CMVN |
Usage
Pass --vad to any FunASR llama.cpp tool to segment long audio internally:
llama-funasr-sensevoice -m sensevoice-small.gguf -a long.wav --vad fsmn-vad.gguf
llama-funasr-cli --enc funasr-encoder-f16.gguf -m qwen3-0.6b-q8_0.gguf -a long.wav --vad fsmn-vad.gguf
Segment boundaries match the PyTorch fsmn-vad front end within ~10 ms.
Links
- 🧩 Runtime & build instructions: FunASR · runtime/llama.cpp — ⭐ Star FunASR if this helps!
- Source model: funasr/fsmn-vad