| --- |
| 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](https://huggingface.co/FunAudioLLM/SenseVoiceSmall)** (SAN-M encoder + CTC) for the zero-Python, CPU/edge **[FunASR llama.cpp runtime](https://github.com/FunAudioLLM/SenseVoice/tree/main/runtime/llama.cpp)** — 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](https://github.com/modelscope/FunASR/tree/main/runtime/llama.cpp)** — 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](https://github.com/modelscope/FunASR/releases)** (tag `runtime-llamacpp-v*`) |
| - **One-page quickstart & benchmarks → [funasr.com/llama-cpp](https://www.funasr.com/llama-cpp.html)** |
|
|
| ```bash |
| 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. |
| ```bash |
| # 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](https://github.com/FunAudioLLM/SenseVoice/blob/main/runtime/llama.cpp/BENCHMARKS.md). |
|
|
| ## Links |
| - 🧩 Runtime & build: **[SenseVoice · runtime/llama.cpp](https://github.com/FunAudioLLM/SenseVoice/tree/main/runtime/llama.cpp)** — ⭐ **Star [SenseVoice](https://github.com/FunAudioLLM/SenseVoice)!** |
| - Source model: [FunAudioLLM/SenseVoiceSmall](https://huggingface.co/FunAudioLLM/SenseVoiceSmall) |
|
|
