Omnivoice Onnx Int8hq

--- language: - vi - en - zh - multilingual pipeline_tag: text-to-speech tags: - tts - onnx - int8 - voice-cloning - omnivoice - cpu library_name: onnxruntime base_model: k2-fsa/OmniVoice license: other license_name: higgs-audio-2-community license_link: LICENSE --- # OmniVoice ONNX (INT8-HQ) — CPU inference **INT8-HQ ONNX** export of [k2-fsa/OmniVoice](https://huggingface.co/k2-fsa/OmniVoice), optimized to run **on CPU** with `onnxruntime` (no GPU, no PyTorch needed at inference time). - Multilingual TTS (646 languages incl. **Vietnamese**) + zero-shot **voice cloning** + voice design. - **24 kHz** output, 8 codebooks, frame rate 75. - INT8-HQ: cosine > 0.9999 vs FP32, perceptually almost indistinguishable. ## Components | Folder | Role | Size | |---|---|---| | `omnivoice_lm_int8_hq/` | Diffusion LM (INT8-HQ, audio head kept FP32) | ~611 MB | | `audio_tokenizer_decoder_int8/` | tokens → 24 kHz waveform | ~82 MB | | `audio_tokenizer_encoder_int8/` | reference audio → codec tokens (voice cloning) | ~378 MB | | `tokenizer.json`, `config.json` | text tokenizer + config | small | > Each model is `model.onnx` + `model.onnx_data` (ONNX external data) — download **both** files. ## ONNX I/O | Model | Input | Output | |---|---|---| | **LM** | `input_ids[batch,8,seq]` int64; `audio_mask[batch,seq]` bool; `attention_mask[batch,1,seq,seq]` bool; `position_ids[batch,seq]` int64 | `logits[batch,8,seq,1025]` f32 | | **Encoder** | `audio[batch,1,num_samples]` f32 @24kHz | `audio_codes[batch,8,num_frames]` int64 | | **Decoder** | `audio_codes[batch,8,num_frames]` int64 | `audio[batch,1,num_samples]` f32 | ## Inference The sampling loop (diffusion + CFG) runs in Python; the LM / encoder / decoder run via ONNX. Reference inference code: [AFun9/Omnivoice-onnx](https://github.com/AFun9/Omnivoice-onnx) (`infer_onnx.py`). Example: ```bash python infer_onnx.py --variant int8hq --num-step 16 --only demo_voice_clone ``` ## Performance (CPU) RTF ~3–7 depending on the CPU (i9-14900KF ~2.8–6.7; slower CPUs are slower). Suitable for batch / offline use, not real-time. Increase `--num-step` for higher quality (slower). ## License This export bundles **two components under different licenses** — you must comply with **both**: - **Diffusion LM** (`omnivoice_lm_int8_hq/`): derived from Qwen3-0.6B / OmniVoice — **Apache-2.0**. - **Audio tokenizer** (`audio_tokeniz...