Reddit 帖称 Kyutai 发布三款更小的 Pocket TTS 模型，最小仅 190 万参数
AI 总结
r/LocalLLaMA 的帖子称，Kyutai 于 10 月 20 日发布三款更小的 Pocket TTS 模型，参数量分别为 190 万、690 万和 1820 万。同一社区帖称，这些是英语模型，支持声音克隆，并以 CPU 运行为设计目标，可在演示中切换不同规模。发帖者表示参数量包含音频解码器，而参考声音编码器是独立的，只需编码一次；目前没有 Kyutai 官方声明或独立测试可供佐证。
深度见解
发帖者认为，把语音生成放在 CPU 上可以把 GPU 留给语言模型，这在聊天模型显存本就紧张时尤为重要。
| Kyutai released three smaller Pocket TTS models on October 20: 1.9M, 6.9M and 18.2M parameters. These are English models, support voice cloning, and are designed to run on CPU. You can switch between the sizes in their demo here. The useful part for me is keeping speech generation on CPU and leaving the GPU to the LLM. Especially when the chat model already barely fits. Having a local assistant read its answer out loud shouldn't require another round of VRAM budgeting. I'd probably start with the 6.9M version. Getting down to 1.9M is impressive, but I'm happy to spend a few million extra parameters on a voice I can listen to for more than thirty seconds. A couple of minutes of speech with names, numbers and awkward punctuation would be a useful comparison. One detail on the size claims: those counts include the audio decoder. The encoder that processes your reference voice is separate, and the reference only needs to be encoded once. Code and setup instructions submitted by /u/BerryBlush_Rogers691 [link] [comments] |