Voiceclonnx Knn Vc
ONNX export of kNN-VC (Baas et al., Interspeech 2023, MIT) for the vconnx voice-conversion library: WavLM-Large layer-6 feature extractor + prematched HiFi-GAN vocoder; the kNN regression step is pure numpy at...
Model source
- Kind
- Other
- File size
- 25.1–387 MB
- Version
- vRevision c0e3406
- Updated
- Oct 25, 2026
- Downloads
- 60
- Source
- Hugging Face
Source description
vconnx · kNN-VC (pure ONNX)
ONNX export of kNN-VC (Baas et al., Interspeech 2023, MIT) for the vconnx voice-conversion library: WavLM-Large layer-6 feature extractor + prematched HiFi-GAN vocoder; the kNN regression step is pure numpy at inference time. Any-to-any voice conversion at 16 kHz, CPU-only.
| file | role | size |
|---|---|---|
wavlm_layer6.onnx | feature extractor (fp32) | 387 MB |
wavlm_layer6_q8.onnx | feature extractor (int8) | 98 MB |
hifigan_knnvc.onnx | vocoder (fp32) | 63 MB |
hifigan_knnvc_q8.onnx | vocoder (int8) | 25 MB |
Export parity vs the torch reference (max abs): WavLM see report · HiFi-GAN see report (full reports in the repo).
Usage
from vconnx import VoiceCloner
out = VoiceCloner(engine="knnvc").clone_voice("source.wav", "reference.wav")
Provenance and upstream license: see PROVENANCE.md. Weights derive from
bshall/knn-vc (MIT) and
microsoft WavLM (MIT).
Sources
1 source
Sources
1 sourceVerified Oct 25
Download files
Model artifacts
4 artifacts
Model artifacts
4 artifactsSource excerpts
3 excerpts
Source excerpts
3 excerpts--- license: mit library_name: onnxruntime tags: - voice-conversion - onnx - vconnx - knn-vc pipeline_tag: audio-to-audio --- # vconnx · kNN-VC (pure ONNX) ONNX export of [kNN-VC](https://github.com/bshall/knn-vc) (Baas et al., Interspeech 2023, MIT) for the **vconnx** voice-conversion library: WavLM-Large layer-6 feature extractor + prematched HiFi-GAN vocoder; the kNN regression step is pure numpy at inference time. Any-to-any voice conversion at 16 kHz, CPU-only. | file | role | size | |---|---|---| | `wavlm_layer6.onnx` | feature extractor (fp32) | 387 MB | | `wavlm_layer6_q8.onnx` | feature extractor (int8) | 98 MB | | `hifigan_knnvc.onnx` | vocoder (fp32) | 63 MB | | `hifigan_knnvc_q8.onnx` | vocoder (int8) | 25 MB | Export parity vs the torch reference (max abs): WavLM see report · HiFi-GAN see report (full reports in the repo). ## Usage ```python from vconnx import VoiceCloner out = VoiceCloner(engine="knnvc").clone_voice("source.wav", "reference.wav") ``` Provenance and upstream license: see `PROVENANCE.md`. Weights derive from [bshall/knn-vc](https://github.com/bshall/knn-vc) (MIT) and [microsoft WavLM](https://github.com/microsoft/unilm/tree/master/wavlm) (MIT).
Source context: 60 downloads · 0 likes · Pipeline audio-to-audio · Library onnxruntime · Repo TigreGotico/voiceclonnx-knn-vc
Source context: 9 downloads · 0 likes · Pipeline audio-to-audio · Library onnxruntime · Repo TigreGotico/voiceclonnx-knn-vc
