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An improved kokoro distillation in 9MB

I'm a 47yo full stack developer that's investing all his free time (and not only that) into thinkering, building, researching with AI. Some days ago I found a paper about distilling kokoro on a ~9MB with around…

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I'm a 47yo full stack developer that's investing all his free time (and not only that) into thinkering, building, researching with AI. Some days ago I found a paper about distilling kokoro on a ~9MB with around 25x RTF. It was very interesting and since the experiment was on a single english voice and I'm Italian, I wanted to see if I could manage to distill it in my language but the training recipe wasn't replicable. So I spent some days researching, experimenting and found the why and even some more tweaks to improve the overall result. The demo I linked shows you how close it is to the original kokoro and you can play straight in the browser (If you use the package locally it's faster) Paper: https://doi.org/10.5281/zenodo.23400040 Code (Apache-2.0): https://github.com/MithrilMan/teacher-in-the-loop Weights: https://huggingface.co/MithrilMan/teacher-in-the-loop pip install teacher-in-the-loop P.S. I wanted to publish the paper on arXiv but I need to be endorsed, would be nice if anyone that can help me could endorse me arxiv.org/auth/endorse?x=GPI7BZ Honestly would be just to be added to the hf papers, I don't seek fame nor fortune lol

Discovery history

  1. Show HN

    Oct 16, 2026 · 1 observations

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