metadata
license: apache-2.0
language:
- zh
- en
library_name: gguf
tags:
- automatic-speech-recognition
- asr
- sensevoice
- funasr
- llama.cpp
- ggml
- cpu
- chinese
pipeline_tag: automatic-speech-recognition
SenseVoiceSmall · GGUF (FunASR llama.cpp runtime)
GGUF build of SenseVoiceSmall (SAN-M encoder + CTC) for the zero-Python, CPU/edge FunASR llama.cpp runtime — multilingual ASR with language / emotion / event tags, ~20× real-time on CPU.
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 sensevoice ./gguf
llama-funasr-sensevoice -m ./gguf/sensevoice-small-q8.gguf --vad ./gguf/fsmn-vad.gguf -a audio.wav
# → 欢迎大家来体验达摩院推出的语音识别模型
Files
| file | size | notes |
|---|---|---|
sensevoice-small-f16.gguf |
470 MB | recommended (f16 matmul weights) |
sensevoice-small-q8.gguf |
~235 MB | recommended — half of f16, same accuracy |
sensevoice-small.gguf |
936 MB | f32 reference |
Usage
The binary prints transcription text directly (no Python detok). --ids for raw ids / --keep-tags for the lang/emotion tags.
# 1. get the VAD too (for long audio): huggingface-cli download FunAudioLLM/fsmn-vad-GGUF
llama-funasr-sensevoice -m sensevoice-small-f16.gguf -a audio.wav --vad fsmn-vad.gguf
On CPU (8 threads) this reaches 8.01 % CER on the 184-clip Mandarin benchmark — vs whisper.cpp 22–31 %. See the benchmark.
Links
- 🧩 Runtime & build: SenseVoice · runtime/llama.cpp — ⭐ Star SenseVoice!
- Source model: FunAudioLLM/SenseVoiceSmall