remsky/kokoro-inno-clone-tuner
text-to-speech model by remsky
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Model card & documentation
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Zero-shot voice tuner for Kokoro-82M. Outputs base Kokoro compatible voice packs @ [510, 1, 256]. (write-up) Same passage for every voice, enrolled from the references. LibriTTS-R speakers are dev-clean held out from training. Code available on Github: remsky/inno-kokoro. Integrated into Kokoro-FastAPI (v0.9.0+) Enrolling a voice: The pack is a plain tensor; torch.save(pack, "voices/amme.pt") makes it a voice file like any other, prefixed by accent and gender like the stock packs. The pitch-tracking ceiling is set automatically from the reference's harmonic spacing, so band-limited or archival sources land in the right octave without tuning. A 5 to 30 s reference clip in, a stock-shaped Kokoro voice pack out. Everything loads from model.safetensors, no extra downloads. Enrollment Architecture Diagram: reference audio to Kokoro-compatible voice pack. Architecture details Enrollment embeds an input audio sample via the baked speaker encoder and maps through model.safetensors to build the encoder side; prosody aspects are measured to…
Read the full model card ↗ · Preview checked 2026-10-31T18:46:29.198Z
Inside the original model card — Document outline
- kokoro-inno-clone-tuner
- Samples
- Usage
- Architecture
- Limits
- Training and Metrics
- Zero-shot identity benchmark
- Licenses and credits
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Model overview
remsky/kokoro-inno-clone-tuner is a text-to-speech model repository published by remsky on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-speech
- Library
- Not reported
- Recent downloads (30 days)
- 1,357,348
- Cumulative likes
- 35
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 9,653,396
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-08-31T02:47:06.000Z
- Last modified
- 2026-10-30T14:55:08.000Z
Compatibility and lineage
Reported languages: en
Reported base models: hexgrad/Kokoro-82M
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:52:33.137Z. Daily imports are snapshots, not real-time monitoring.
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