Refresh the pinned llama.cpp revision with AMD Vulkan submission batching and DeviceLost diagnostics, adapt the sampler API, and document Windows troubleshooting. Refs #3479.
* feat(runtime): add Windows Vulkan release asset
* fix(ci): install SPIR-V headers for Windows Vulkan
* fix(runtime): make Windows Vulkan package standalone
Document the current sm_86 Windows CUDA prebuilt limit and direct RTX 50 / Blackwell users to CPU binaries or source builds with CMAKE_CUDA_ARCHITECTURES=120 until a dedicated asset is available.
Adds a Windows x64 CUDA release asset for the llama.cpp SenseVoice runtime, with CUDA Toolkit setup, architecture-86 build flags, focused SenseVoice target packaging, docs, and workflow regression tests. Manual workflow dispatch 29656771776 passed all build matrix jobs including build-windows-x64-cuda.
Make the runtime a downloadable product (whisper.cpp-style), no manual export needed:
- download-funasr-model.sh: one command to pull pre-converted GGUF from Hugging Face
(FunAudioLLM/*-GGUF), incl. fsmn-vad for built-in --vad. No Python ML env required.
- convert-funasr-to-gguf.py: one-step HF/ModelScope checkpoint -> GGUF (wraps the
validated export_*.py; discovered relative to itself so it works in any layout).
- CMakeLists.txt: standalone, CI-friendly top-level build. FetchContent pins llama.cpp
(provides ggml + llama), static libs -> self-contained binaries in build/bin/, no
hardcoded paths; builds on Linux/macOS/Windows x64/arm64. `cmake -B build && cmake --build build -j`.
- README: download-first + standalone-build quickstart; links to the HF GGUF repos.
Verified on Linux: all targets build via FetchContent (static, no shared-lib deps);
hf download -> run reproduces canonical output. Additive; runtime/llama.cpp/ only.
Add a native ggml FSMN-VAD front end so the binaries segment long audio themselves,
with no Python at runtime. New `--vad fsmn-vad.gguf` flag on llama-funasr-cli,
llama-funasr-sensevoice and llama-funasr-paraformer runs FSMN-VAD (fbank + LFR + CMVN +
FSMN encoder + E2EVadModel state machine, in funasr-common/funasr_vad.h) and decodes
each speech segment, then concatenates.
- funasr-common/funasr_vad.h: single-header VAD; segment boundaries within ~10 ms of
PyTorch fsmn-vad.generate on the 184-clip set (DEFAULT_SILENCE_SCHEDULE replicated,
chunk-stepped silence schedule + speech_noise_thres 0.5).
- funasr-vad/: standalone VAD tool (wav -> [start_ms,end_ms] segments).
- export_vad_gguf.py: export FSMN-VAD encoder + CMVN to GGUF (1.7 MB, 24 tensors).
- BENCHMARKS.md: bare binary with built-in VAD reaches the reference end-to-end —
full-184 micro-CER SenseVoice 8.01 / Paraformer 9.85 / Fun-ASR-Nano 8.30.
Additive only: no existing code is modified outside runtime/llama.cpp/.
LauraGPT