Publish FunASR 1.4.16 bilingual site guide

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web-pages/product-site/data/blog.json

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+      "zh": {
+        "title": "v1.4.16：混合设备子模型修复",
+        "summary": "保持 VAD、标点和说话人子模型的显式设备配置，并补齐原生 Transformers 指南。"
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+        "title": "v1.4.16: Mixed-device submodel fix",
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web-pages/product-site/legacy/blog/funasr-v1-4-16-submodel-device-release.html

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+<!DOCTYPE html>
+<html lang="zh">
+<head>
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+  <title>FunASR v1.4.16：混合设备子模型与原生 Transformers 指南 | FunASR</title>
+  <meta name="description" content="FunASR v1.4.16 修复混合设备流水线中的 VAD、标点与说话人子模型设备保持，并发布经过测试的原生 Transformers 指南。">
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+<nav class="nav"><div class="container"><a href="/" class="nav-logo">Fun<span>ASR</span></a><div class="nav-links"><a href="/deploy/">部署</a><a href="/models.html">模型</a><a href="/benchmarks.html">性能</a><a href="/ecosystem.html">生态</a><a href="/blog/">博客</a></div><a href="/en/blog/funasr-v1-4-16-submodel-device-release.html" style="font-size:.83rem;font-weight:500;color:var(--text-soft)">EN</a><a href="/go/github" target="_blank" rel="noopener" class="nav-btn">GitHub ★</a></div></nav>
+<article><div class="container">
+  <h1>FunASR v1.4.16：混合设备子模型与原生 Transformers 指南</h1>
+  <p class="post-meta">2026-09-18 · FunASR 正式发布</p>
+  <img class="hero-media" src="/img/banner.4f436d19.png?v=1.4.16" alt="FunASR v1.4.16 发布视觉图">
+  <p class="lead">v1.4.16 让显式配置的 VAD、标点和说话人 submodel 在重复推理与运行时覆盖之间保持各自设备，并补齐标点行为和原生 Transformers 接入文档。</p>
+  <h2>安装</h2>
+  <pre><code>python -m pip install -U "funasr==1.4.16"</code></pre>
+  <p>公开包位于 <a href="https://pypi.org/project/funasr/1.4.16/" target="_blank" rel="noopener">PyPI 1.4.16</a>。wheel SHA-256 为 <code>f95943f6a8111349a1b08907363b048a49e9cb9caa1e3afd8c92970d08bf450d</code>，sdist SHA-256 为 <code>1e2f8e3887fbc4b164cce40f73bf1324907da6ab59d1e8bf2add827f534c69e7</code>。</p>
+  <h2>这次修复什么</h2>
+  <ul><li><code>vad_kwargs</code>、<code>punc_kwargs</code> 与 <code>spk_kwargs</code> 的显式设备放置在重复调用中保持稳定。</li><li>运行时 <code>device</code> 覆盖不再改写已加载模型或调用方持有的子模型配置。</li><li>说话人推理使用说话人模型自身配置；中英文指南说明何时需要 CT-Transformer 标点后处理，以及如何验证原生 Transformers 路径。</li></ul>
+  <div class="proof">设备回归由 CPU 权重替身与模拟加速器可用性验证；它覆盖配置传播、回退和重复调用，但不是 CUDA、MPS 或 NPU 性能认证。</div>
+  <h2>签名源码与可校验资产</h2>
+  <p>签名标签 <code>v1.4.16</code> 精确指向 <code>904cd18681b8083de5e1039bd0ecebc4f49ede60</code>。<a href="https://github.com/modelscope/FunASR/releases/tag/v1.4.16" target="_blank" rel="noopener">Release</a> 恰有 12 个资产：两个 Python 制品、九个来自 <a href="https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.6" target="_blank" rel="noopener">runtime-llamacpp-v0.2.6</a> 的独立版本运行时，以及一份清单。</p>
+  <ul><li>Python：<code>funasr-1.4.16-py3-none-any.whl</code>、<code>funasr-1.4.16.tar.gz</code></li><li>Linux：<code>funasr-llamacpp-linux-arm64.tar.gz</code>、<code>funasr-llamacpp-linux-x64.tar.gz</code>、<code>funasr-llamacpp-linux-x64-avx2.tar.gz</code>、<code>funasr-llamacpp-linux-x64-vulkan.tar.gz</code></li><li>macOS：<code>funasr-llamacpp-macos-arm64.tar.gz</code></li><li>Windows：<code>funasr-llamacpp-windows-x64.zip</code>、<code>funasr-llamacpp-windows-x64-avx2.zip</code>、<code>funasr-llamacpp-windows-x64-cuda.zip</code>、<code>funasr-llamacpp-windows-x64-vulkan.zip</code></li><li>校验：<code>SHA256SUMS</code></li></ul>
+  <p>九个原生运行时未携带本次 Python 修复；请先用清单校验，再在目标硬件和真实音频上验收。</p>
+  <div class="cta"><p>从固定版本和校验清单开始复现。</p><a class="btn" href="https://github.com/modelscope/FunASR/releases/tag/v1.4.16" target="_blank" rel="noopener">查看 v1.4.16 的 12 个资产</a></div>
+</div></article>
+<footer><div class="container">© 2024-2026 Tongyi Lab, Alibaba Group · <a href="https://github.com/modelscope/FunASR/blob/main/LICENSE">MIT License</a></div></footer>
+</body>
+</html>

web-pages/product-site/legacy/blog/index.html

@@ -49,6 +49,7 @@
 </style></head><body>
 <nav class="nav"><div class="container"><a href="/" class="nav-logo">Fun<span>ASR</span></a><div class="nav-links"><a href="/#capabilities">核心能力</a><a href="/#usage">如何使用</a><a href="/#benchmark">性能</a><a href="/#demo">演示</a><a href="https://modelscope.github.io/FunASR/zh/" target="_blank">文档</a><a href="/quickstart.html">快速上手</a><a href="/models.html">模型</a><a href="/ecosystem.html">生态</a><a href="/blog/">技术博客</a><a href="/vs-whisper.html">对比 Whisper</a><a href="/donors.html">功德榜</a></div><a href="https://www.funasr.com/en/blog/" style="font-size:0.83rem;font-weight:500;color:var(--text-soft)">EN</a><a href="/go/github" target="_blank" class="nav-btn">GitHub ★</a></div></nav>
 <section class="launch-feature"><a href="/blog/funclip-v2-2-0-moss-speaker-clipping.html"><div><span class="date">2026-08-31 · FunClip v2.2.0</span><h2>MOSS 多说话人转写进入 FunClip：从一句话到带说话人的片段</h2><p>通过经真实双说话人音频验证的 vLLM 路径，把第三方 MOSS 模型的段级时间戳和说话人标签直接用于 SRT 与说话人片段导出。</p></div><span class="action">查看部署与剪辑边界 →</span></a></section>
+<section class="previous-release"><div class="container"><a class="post-card" href="/blog/funasr-v1-4-16-submodel-device-release.html"><span class="date">2026-09-18 · 正式 Release</span><h2>FunASR v1.4.16：混合设备子模型与原生 Transformers 指南</h2><p>保持 VAD、标点和说话人子模型的显式设备配置，公开可校验的 PyPI 制品、九个运行时与清单。</p></a></div></section>
 <section class="previous-release"><div class="container"><a class="post-card" href="/blog/meeting-transcript-acceptance.html"><span class="date">2026-09-09 · 应用工程</span><h2>HTTP 200 不等于转写成功：会议录音的验收清单</h2><p>区分文本、匿名说话人、时间戳和尾部覆盖；用经过测试的 Python 检查器开始验收，不把结构合法当作质量合格。</p></a><a class="post-card" href="/blog/funasr-v1-4-14-portable-source-release.html"><span class="date">2026-09-04 · 正式 Release</span><h2>FunASR v1.4.14：可移植源码包、MOSS 入口与十平台运行时</h2><p>修复 Git archive 与源码安装的可移植性，补齐 MOSS 服务入口，并提供 PyPI 包、十平台运行时与 SHA-256 清单。</p></a><a class="post-card" href="/blog/funasr-v1-4-5-pypi-llama-cpp-release.html"><span class="date">2026-08-28 · 正式 Release</span><h2>FunASR v1.4.5：更轻的 Python 推理与九平台 llama.cpp 运行时</h2><p>默认安装不再硬依赖 torchaudio，可选 kaldi-native-fbank，并提供 PyPI 包、九平台运行时与 SHA-256 清单。</p></a><a class="post-card" href="/blog/funasr-v1-4-3-pypi-release.html"><span class="date">2026-08-21 · 正式 Release</span><h2>FunASR v1.4.3：可选 Silero VAD 与大规模固定 K 说话人聚类</h2><p>新增毫秒级 Silero VAD 适配器，降低已知说话人数的大规模聚类内存压力，并提供 12 个带 SHA-256 的发布资产。</p></a><a class="post-card" href="/blog/funasr-v1-4-0-pypi-release.html"><span class="date">2026-07-31 · 正式 Release</span><h2>FunASR v1.4.0：更完整的 PyPI 安装包与更安全的 AutoModel 参数</h2><p>修复 SenseVoice 与 RWKV-BAT 包数据，提前拒绝 vda_model 误拼写，并提供 12 个带 SHA-256 的发布资产。</p></a></div></section>
 <section class="ecosystem-feature"><div class="container"><a class="post-card" href="/blog/fun-asr-nano-transformers.html"><span class="date">2026-09-09 · 生态技术与应用</span><h2>Fun-ASR-Nano + Transformers：先选对权重，再接入应用</h2><p>原生 Transformers 支持已合并：分清 -hf、原始权重、vLLM 和 GGUF，理解音频预处理、生成结果与应用验收，附固定版本接入指南。</p></a></div></section>
 <section class="ecosystem-feature"><div class="container"><a class="post-card" href="/blog/subtitle-edit-fun-asr-sensevoice-local-subtitles.html"><span class="date">2026-08-03 · 生态集成</span><h2>Subtitle Edit 5.2：Fun-ASR Nano / SenseVoice 本地视频字幕</h2><p>在 Windows、macOS 与 Linux 的成熟字幕工作区中直接选择本地 ASR 引擎，支持 Q4、Q8、F16。</p></a></div></section>