v1.4.16
0xPlaygrounds/rigv1.4.16Sep 18, 2026by github-actions[bot]
Upgrading?
AI Summary
This release enhances reliability in mixed-device inference pipelines and clarifies punctuation model requirements. It also introduces new English and Chinese adoption guides for native Transformers.
Key Highlights
- Reliable mixed-device pipelines that preserve explicit `vad_kwargs`, `punc_kwargs`, and `spk_kwargs` device placement across repeated inference calls.
- Clearer documentation explaining when SenseVoiceSmall or Paraformer output requires the CT-Transformer punctuation postprocessor.
- New native Transformers adoption guides connecting model discovery, version requirements, and installation steps.
- Runtime downloads paired with llama.cpp v0.2.6 for multiple platforms.
Breaking Changes
- Runtime `device` overrides no longer mutate the placement of already-loaded models.
- Caller-owned submodel configuration behavior modified to stay unchanged.
New Features
- Native Transformers adoption guides
- Runtime binaries for Linux, macOS, and Windows
Full Release Notes
# FunASR 1.4.16 ## Highlights - **Reliable mixed-device pipelines:** explicit `vad_kwargs`, `punc_kwargs`, and `spk_kwargs` device placement is preserved across repeated inference calls. Runtime `device` overrides no longer mutate the placement of already-loaded models, caller-owned submodel configuration stays unchanged, and speaker inference uses the speaker model's own configuration. - **Clearer punctuation behavior:** documentation now explains when SenseVoiceSmall or Paraformer output needs the CT-Transformer punctuation postprocessor instead of assuming every model emits punctuation natively. - **Native Transformers adoption guides:** new tested English and Chinese guides connect model discovery, version requirements, CUDA installation, local downloads, and bounded acceptance checks. ## Install ```bash python -m pip install -U "funasr==1.4.16" ``` Install a PyTorch/TorchAudio build appropriate for your hardware and the selected model's optional dependencies. ## Verification boundaries - Mixed-device regressions were exercised with CPU-resident stand-in weights and mocked accelerator availability. They verify configuration propagation, fallback, repeated calls, and model/config consistency; they are not a CUDA, MPS, or NPU performance certification. - Native Transformers guidance is versioned source documentation. Follow each model's documented revision and hardware requirements; it does not claim that every model/backend combination is interchangeable. - Native downloads retain their independently versioned `runtime-llamacpp-v0.2.6` source commit `a57c05bfe2a91b5e0cb0983479634eba3e28ede5`. They are unchanged native binaries, not builds from the Python 1.4.16 commit and not carriers of Python-only fixes. The separate Blackwell archive remains on the runtime release and is not attached here. Previous Python release: [1.4.15](https://github.com/modelscope/FunASR/releases/tag/v1.4.15). For a regression, retain the last working environment and report the exact artifact, model revision, platform, and reproduction. [Full source changes](https://github.com/modelscope/FunASR/compare/v1.4.15...v1.4.16) <!-- funasr-runtime-downloads:start --> ## Runtime downloads This Python release pairs with the current prebuilt llama.cpp / GGUF runtime release: [runtime-llamacpp-v0.2.6](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.6). The same nine verified runtime assets are attached directly to this Python release. | Platform | Asset | SHA-256 | |---|---|---| | Linux arm64 | [funasr-llamacpp-linux-arm64.tar.gz](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-linux-arm64.tar.gz) | `7bca29cfa3c9a08e235a62212ca9e00f6656e59a8f07078966a2bfda1e5aa1f9` | | Linux x64 AVX2 | [funasr-llamacpp-linux-x64-avx2.tar.gz](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-linux-x64-avx2.tar.gz) | `aaebc5470f846ce915200b35d6e9f9bd0a0d3ed399d39e49bdeb7a1f1782bc70` | | Linux x64 Vulkan | [funasr-llamacpp-linux-x64-vulkan.tar.gz](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-linux-x64-vulkan.tar.gz) | `f02d41e98e9d4041f0896661007193810f025484d2175958f7c1313d5c90ec46` | | Linux x64 portable | [funasr-llamacpp-linux-x64.tar.gz](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-linux-x64.tar.gz) | `779967de1c528c2be966bcc47f246e7d3e6fcdb748d9491263062f4120f35e52` | | macOS arm64 | [funasr-llamacpp-macos-arm64.tar.gz](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-macos-arm64.tar.gz) | `bda59474202b887190f59d25b7b42c714469efae71276072c12fa0a38de68792` | | Windows x64 AVX2 | [funasr-llamacpp-windows-x64-avx2.zip](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-windows-x64-avx2.zip) | `062cda8fefadd31c3e811227116daccf448a8520f4b0bb168d225c896e65ebbd` | | Windows x64 CUDA | [funasr-llamacpp-windows-x64-cuda.zip](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-windows-x64-cuda.zip) | `148657911fb666b7af6ec43af2e23a0984e3259012b4c39f95631b717feb6840` | | Windows x64 Vulkan | [funasr-llamacpp-windows-x64-vulkan.zip](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-windows-x64-vulkan.zip) | `debf8007e55011cad06081e7b8a78972f1b8fe672bc324d41e650d68821f6a6a` | | Windows x64 portable | [funasr-llamacpp-windows-x64.zip](https://github.com/modelscope/FunASR/releases/download/v1.4.16/funasr-llamacpp-windows-x64.zip) | `f6a73a548413ba9fbaf2145263ea66ec53cbdad1fb11790dbeeee493e339492e` | For Python users, install from PyPI: ```bash python -m pip install -U "funasr==1.4.16" ``` <!-- funasr-runtime-downloads:end --> ## Artifact verification `SHA256SUMS` covers the wheel, sdist, and nine attached native archives. The Python artifacts are: - `funasr-1.4.16-py3-none-any.whl`: `f95943f6a8111349a1b08907363b048a49e9cb9caa1e3afd8c92970d08bf450d` - `funasr-1.4.16.tar.gz`: `1e2f8e3887fbc4b164cce40f73bf1324907da6ab59d1e8bf2add827f534c69e7` PyPI and GitHub Python artifact bytes must match after publication.
Related Repositories
A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io
An open-source remote desktop application designed for self-hosting, as an alternative to TeamViewer.
Build smaller, faster, and more secure desktop and mobile applications with a web frontend.
π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — all without a single pixel of video.
Incredibly fast JavaScript runtime, bundler, test runner, and package manager – all in one