KittenML

Stars and mentions

Last 30 days, Oct 5 – Nov 3

GitHub stars0
mentions7
01234Oct 5Oct 19Nov 3
UTC days · repositories KittenML owns0 repositories

Package downloads

Cumulative recorded downloads · since 2026-04-09

PyPI10.2K
02.6K5.1K7.7K10.2KOct 5Oct 19Nov 3
Oct 30PyPI: 1/1 packages observed

Across 1 known packages in repositories KittenML owns. Cumulative totals include recorded downloads before the selected range. Missing observations leave gaps; totals may be incomplete. PyPI excludes known mirrors.

Top repositories

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Contributes to

Repositories outside KittenML’s account where KittenML opened or reviewed pull requests in the past 365 days.

Who noticed KittenML

Everyone who starred or forked KittenML’s repositories since the archive began in 2011.

Notable accounts

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Biggest fans

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Breakout weeks

Each repository’s best week of new stars, with the release published around it.

Mentions

7posts
Nov 40 posts
  1. حجمه فقط 25 م.ب نموذج ذكاء إصطناعي خفيف مهمته تحويل النص إلى صوت ويدعم اللغة العربية كلغة مدعومة من ضمن 20 لغة في النموذج سيفيد من يريد دمجه مع تطبيق هاتف ذكي أو برنامج كمبيوتر ويحتاج مكتبات خفيفة الحجم رابط المشروع: KittenML/KittenTTS #تقنية #ذكاء_اصطناعي t.co

    12 likes · 1,494 views
  2. @fmontes @ElevenLabs Y no, podrias clonarla Creo que este repo te podría servir KittenML/KittenTTS

    1 like · 69 views
  3. You want voice cloning without fine-tuning. KittenTTS gives you that from a short clip. With more than 10,000 stars on GitHub, it's a popular open-source text-to-speech library with two model families behind one constructor. KittenML/KittenTTS t.co

    1 like · 21 views
  4. 1.7Bの音声AIがGPUなしでリアルタイム動作。 KittenTTS 2は1.58bitの3値重みで軽量化。日本語にも対応し、5〜30秒の音声から声のクローンまで可能。感情表現も制御できる。 ローカル音声AIの進化がすごい。ただし重みは独自ライセンスなので注意。 GitHub KittenML/KittenTTS

    31 views
  5. Reddit · · r/LocalLLaMA · u/ElectricalBar7464 · KittenML/KittenTTS

    Kitten-TTS 2: New Open-source SOTA 1.58 bit TTS (CPU-only with voice cloning, multilingual, emotion control) KittenML has just released code and weights of Kitten-TTS 2, which is a super-efficient frontier TTS model, and the world's first 1.58-bit TTS model. It runs in real time on just a CPU, with zero-shot voice cloning, multilingual support, and expressive / emphasis control. Code and weights are open-source. Ternary(1.58-bit) Weights means it can run locally or be self-hosted for super-cheap. Github: KittenML/KittenTTS Hugging Face: huggingface.co KittenML's Discord: discord.com Key features and Advantages 1. Ternary TTS: Every linear weight in the body is one of three values (-1, 0, +1) with group size of 128 for scales. Tiny footprint and fast CPU inference. The model has 1.7B parameters. 2. Real-time on CPU and consumer GPU's too: No GPU needed for real-time generation. Optimized ternary kernels for CPU inference provided. 3. Expressive voice cloning: zero-shot cloning from less than 5 seconds of reference audio, and it keeps the expressivity, accent information etc. No fine-tuning needed. 4. Multilingual TTS: Model supports voice cloning in 20+ languages. Cross-language voice cloning can be used to create accented speech too. 5. Expressive / emphasis control: you can steer the delivery and stress specific words, not just pick a voice. Details in the Readme. 6. Open source (hell yeah!): code and weights are open-source and free to use. It's an oss alternative to elevenlabs for gpu-poor folks. easy to self-deploy or run locally. 7. What changed from V0.8 to 2: higher quality. Completely new architecture, natural sounding speech, ternary weights, zero-shot voice cloning, multilingual, and emphasis/emotion control.

    704 points · 145 comments
  6. 15M parameters and under 25MB? That’s impressive. 🔥 Small, expressive TTS models like this could make local AI voice generation much more accessible to developers. @divamgupta KittenML/KittenTTS

    1 like · 26 views

Achievements

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Silver
32nd place finishes
Bronze
13rd place finishes
Awarded repositories
1Owned by KittenML now

Repositories

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  1. KittenTTSBest: 2nd by stars, 1,263 stars031

Every award

Top-three finishes of these repositories in completed trending days and weeks, newest first.

  1. KittenTTS
  2. KittenTTS
  3. KittenTTS
  4. KittenTTS

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