You can deploy this model and start earning money today!

vasyadeva/
StyleTTS2-UA-Denys

Name: StyleTTS2-UA-Denys
Availability: InStock

patriotyk/styletts2_ukrainian_multispeaker_hifigan

quantized

mit

Views

No views yet

StyleTTS2 Ukrainian (multispeaker) — ONNX export

An ONNX export of patriotyk/styletts2_ukrainian_multispeaker for on-device inference (ONNX Runtime, e.g. iOS). This repository adds no new training — it is a faithful export of patriotyk's PyTorch weights, plus a small graph fix so the model loads in ONNX Runtime.

All credit for the model, training data, and Ukrainian front-end belongs to @patriotyk. Please cite and support the original work.

Source

Model: patriotyk/styletts2_ukrainian_multispeaker
Inference / export code: patriotyk/styletts2-inference
Front-end (stress + IPA): patriotyk/ukrainian-word-stress, patriotyk/ipa-uk
Demo: patriotyk/styletts2-ukrainian

What was changed

Exported the PyTorch model to ONNX with torch.onnx.export (opset 19), using patriotyk's own export_onnx.py procedure.
Applied the one required graph fix: a Transpose node whose perm contained -1 (which ONNX Runtime rejects) was rewritten to 2. This is the same patch patriotyk's export script applies. The file here is already patched — no post-processing is needed to load it in ORT.

Files

file	description
`model.onnx`	the exported + patched model (330 MB)
`config.yml`	model config (vocab, params) — from the source repo
`style_denys.pt` / `style_denys.bin`	the "Денис Денисенко" speaker style vector (`s_prev`, 256 float32), as `torch` tensor and raw little-endian floats

Inputs / outputs

name	type	shape
`tokens`	int64	`[seq_length]`
`speed`	float32	scalar
`s_prev`	float32	`[1, 256]` (a speaker style vector)
`output_wav`	float32	`[seq_length]` — 24 kHz mono PCM

Tokens are produced by patriotyk's front-end (ukrainian-word-stress → ipa-uk → tokenizer over the config.yml vocab).

License

MIT, inherited from the source model. See LICENSE.

vasyadeva/StyleTTS2-UA-Denys