pocket-tts-GGUF

模型介绍

Pocket TTS is a lightweight (~100M param) continuous-latent autoregressive TTS model from Kyutai, based on the CALM paper (arXiv:2509.06926). Unlike codebook-based TTS models, Pocket TTS emits continuous float vectors — no discrete tokens, no softmax sampling: - **FlowLM backbone** — causal transformer (1024D, 16 heads, 6 layers; 24 layers for the French preview, RoPE, GELU) operating at 12.5 Hz - **Consistency head** — SimpleMLPAdaLN (512D, 6 ResBlocks) with timestep embedding → one-step LSD decode → 32-dim continuous latent vectors - **Mimi VAE decoder** — SEANet upsample convolutions + 2-layer transformer → 24 kHz PCM - **Mimi VAE encoder** *(voice-cloning builds only)* — SEANet downsample + 2-layer transformer + speaker projection → reference conditioning - **Text tokenizer** — SentencePiece BPE (4000 vocab, embedded in GGUF) Single GGUF file — no separate codec companion needed (Mimi weights and the tokenizer are embedded). Pocket TTS is zero-shot: it clones the timbre of a short reference clip. The **voice-cloning builds** (the files *without* `novc` in the name) embed the Mimi VAE **encoder** and speaker projection needed to condition on a reference; the English-only `novc` builds omit that encoder and are ~20 MB smaller.

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：cc-by-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。