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cangmeng/SenseVoiceSmall-GGUF
SenseVoiceSmall-GGUF is a automatic speech recognition model from cangmeng. Use it when you need speech turned into text. It is set up for gguf. The card lists the license as apache-2.0.
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.
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.gguf1.7 GB · 100%
From the Hugging Face model README
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.
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:
runtime-llamacpp-v*)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
| 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 |
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.