Wav2vec2 Large Voxrex Swedish Onnx

--- license: cc0-1.0 language: - sv tags: - onnx - onnx-asr - wav2vec2 - automatic-speech-recognition base_model: - KBLab/wav2vec2-large-voxrex-swedish --- # wav2vec2-large-voxrex-swedish-onnx (ONNX) ONNX export of [KBLab/wav2vec2-large-voxrex-swedish](https://huggingface.co/KBLab/wav2vec2-large-voxrex-swedish), a Swedish wav2vec2 CTC ASR model from KBLab (National Library of Sweden), for use with [onnx-asr](https://github.com/istupakov/onnx-asr) (`wav2vec2-ctc` model type). Per-utterance zero-mean/unit-variance normalization is baked into the ONNX graph, masked by `input_lengths` for correct behavior with padded/batched input, so the model works with onnx-asr's plain `identity` preprocessor (raw 16kHz waveform in). ## Usage ```py import onnx_asr model = onnx_asr.load_model("OpenVoiceOS/wav2vec2-large-voxrex-swedish-onnx") print(model.recognize("test.wav")) ``` ## Files * `model.onnx` / `model.onnx.data` — fp32 ONNX graph (inputs: `input_values` (batch, samples) float32, `input_lengths` (batch,) int64; output: `logprobs` (batch, frames, vocab) float32 log-softmax). * `vocab.txt` — CTC vocabulary in onnx-asr's `token id` format (word-delimiter -> `▁`, pad token -> `<blk>`). * `config.json` — `{"model_type": "wav2vec2-ctc", "subsampling_factor": 320}`. No int8 quantized variant is included yet -- `onnxruntime.quantization` does not currently support the `torch.onnx` dynamo-exported graph for this architecture. ## License CC0 1.0 Universal (public domain), inherited from the base model.

Source context: 11 downloads · 0 likes · Pipeline automatic-speech-recognition · Repo OpenVoiceOS/wav2vec2-large-voxrex-swedish-onnx