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FunASR llama.cpp runtime v0.2.3

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@github-actions github-actions released this 28 Aug 18:30
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runtime-llamacpp-v0.2.3
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Prebuilt self-contained binaries for the FunASR llama.cpp / GGUF runtime: SenseVoice, Paraformer, and Fun-ASR-Nano with built-in FSMN-VAD.

v0.2.3

  • Extends SenseVoice diagnostics beyond backend initialization with flushed model ready, graph allocated, and compute starting stage boundaries.
  • These boundaries separate model loading, graph allocation, and graph execution failures after a CUDA or Vulkan backend reports ready.
  • Built from exact commit 820f1c64a3123112a3099bc3fdc373dafa381768; all nine platform builds and the release job succeeded.
  • The Windows Vulkan package is ready for Radeon 780M and RX 9070 XT retesting. This diagnostic release does not claim to fix the AMD Windows 0xC0000005 crash.
  • Android/Mali remains outside the official prebuilt and continuously validated targets.

For --backend vulkan or --backend cuda, the last stderr boundary reached narrows the failure stage:

  • Before backend ready: backend selection, initialization, or default buffer-type resolution.
  • backend ready without model ready: model loading.
  • model ready without graph allocated: graph allocation.
  • graph allocated without compute starting: preparation immediately before graph execution.
  • compute starting: the failure is inside graph execution or a lower driver/backend layer.

Quick start

Download the default quantized model with:

bash download-funasr-model.sh <sensevoice|paraformer|nano>

The helper requires the Hugging Face CLI (pip install -U huggingface_hub). Then run llama-funasr-cli, llama-funasr-sensevoice, or llama-funasr-paraformer.

Use the default x64 asset for maximum CPU compatibility. Use x64-avx2 on CPUs with AVX2/FMA/F16C/BMI2. Vulkan assets require a working Vulkan driver/ICD. The Windows CUDA asset targets CUDA architecture 86 and requires a compatible NVIDIA driver; build from source for other GPU architectures.

SHA-256

54abd8dbdcfc200a64a62b657f40d6e4c123c423988707058ce2771096f2921a  funasr-llamacpp-linux-arm64.tar.gz
139616c8adf6b5b306cefcfb1813fabc0f4b7727d655d79102163c5c146df200  funasr-llamacpp-linux-x64-avx2.tar.gz
ea8eeb9e334598a59c4cdb2dba282855b9a3b909cd05684d30250914f418bf43  funasr-llamacpp-linux-x64-vulkan.tar.gz
5b7cf0c2339ab76d8a56594455b1607e02f1eab34392b2543b95a5273413f088  funasr-llamacpp-linux-x64.tar.gz
532da7810e9311b275e3dd2e6f693811421ab49881e0194a788a6db189df4000  funasr-llamacpp-macos-arm64.tar.gz
55fa78e2a7522e54ead84532452afe40041a60014ba0261add611124897a7fe8  funasr-llamacpp-windows-x64-avx2.zip
ee25ed9cb4dff763f94de7db5812dd69fd7e748d2940dfbf82f29c408a4d419e  funasr-llamacpp-windows-x64-cuda.zip
1c90daf2292fcf9041c14a8017be65a05acc8e42443ee0bbc8a8dfddb78cbdc7  funasr-llamacpp-windows-x64-vulkan.zip
54520b705ffedfc2b3505f337bfff64d7890e28b660e78e7255b27e1dc34dc0e  funasr-llamacpp-windows-x64.zip

Build evidence: https://github.com/modelscope/FunASR/actions/runs/33197306623

Docs: https://github.com/modelscope/FunASR/blob/runtime-llamacpp-v0.2.3/runtime/llama.cpp/README.md

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