{"id":50110729,"title":"Show HN: An improved kokoro distillation in 9MB","points":1,"user":"mithrilman","time":1792100483,"time_ago":"10 hours ago","type":"link","content":"

I'm a 47yo full stack developer that's investing all his free time (and not only that) into thinkering, building, researching with AI.\nSome 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.\nSo I spent some days researching, experimenting and found the why and even some more tweaks to improve the overall result.\nThe 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\nCode (Apache-2.0): https://github.com/MithrilMan/teacher-in-the-loop\nWeights: https://huggingface.co/MithrilMan/teacher-in-the-loop

pip install teacher-in-the-loop

P.S.\nI 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\nHonestly would be just to be added to the hf papers, I don't seek fame nor fortune lol","url":"https://huggingface.co/spaces/MithrilMan/teacher-in-the-loop","domain":"huggingface.co","comments":[{"id":50113347,"level":0,"user":"yloopz","time":1792118826,"time_ago":"5 hours ago","content":"

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