Tags: QwenAudio/Fun-ASR
Tags
docs(examples): add runnable Fun-ASR-Nano examples Add runnable Python examples for quickstart, direct inference, speaker diarization, vLLM batch inference, and streaming SDK. Add examples/README.md, README links for all languages, and smoke tests covering documented example entrypoints and stale vLLM snippets.
docs(examples): add runnable Fun-ASR-Nano examples Add runnable Python examples for quickstart, direct inference, speaker diarization, vLLM batch inference, and streaming SDK. Add examples/README.md, README links for all languages, and smoke tests covering documented example entrypoints and stale vLLM snippets.
test: numerical regression harness (frozen golden vs ggml/VAD/CIF/CTC… … output) (#124) Adds tests/ — runs each runtime tool on a fixed 6 s clip and diffs against frozen golden output, catching regressions in the ggml graphs, the FSMN-VAD state machine, the CIF predictor and CTC decode. - tests/run_regression.sh: auto-detects which tools are built; VAD model is auto-fetched (1.7 MB), ASR GGUFs tested when present or with RUN_FULL=1 (downloads from HF). Non-zero exit on any mismatch. BIN_DIR/MODELS_DIR overridable. - tests/sample.wav (~6 s) + tests/golden/*.txt: golden captured on Linux x86-64 with the f16 GGUFs from FunAudioLLM/*-GGUF. Verified locally: all present tools PASS; default mode fetches VAD + skips absent models.