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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...

ArtOtherVersionRevision c0e3406BBewertung

Modellquelle

Art
Other
Dateigröße
25,1–387 MB
Version
vRevision c0e3406
Aktualisiert
25. Okt. 2026
Downloads
60
Quelle
Hugging Face

Quellenbeschreibung

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.

filerolesize
wavlm_layer6.onnxfeature extractor (fp32)387 MB
wavlm_layer6_q8.onnxfeature extractor (int8)98 MB
hifigan_knnvc.onnxvocoder (fp32)63 MB
hifigan_knnvc_q8.onnxvocoder (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).

Quellen

1 Quelle
Hugging FacePrimärVersion c0e3406e7326cdb98c75b42ccf9ff207ff40003a
huggingface.co/TigreGotico/voiceclonnx-knn-vc/tree/c0e3406e7326cdb98c75b42ccf9ff207ff40003a

Verifiziert 25. Okt.

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Modellartefakte

4 Artefakte

hifigan_knnvc_q8.onnx

onnx · 25,1 MB · SHA-256 93fe768fd462…7e43 · Hugging Face

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hifigan_knnvc.onnx

onnx · 63,1 MB · SHA-256 47ac3ce468e9…6671 · Hugging Face

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wavlm_layer6_q8.onnx

onnx · 97,5 MB · SHA-256 b16c392b7402…5a5f · Hugging Face

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wavlm_layer6.onnx

onnx · 387 MB · SHA-256 5c0cc7c6648c…8743 · Hugging Face

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Quellenauszüge

3 Auszüge

--- 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