STT/ASR - onnx
Collection
OVOS STT/ASR models for onnx-asr (ONNX runtime). Most ship fp32 + int8 (set quantization: int8 for faster/smaller CPU inference). • 233 items • Updated • 2
ONNX export of Qwen/Qwen3-ASR-0.6B-hf for
onnx-asr with the speech-llm model type (requires the
speech-llm model-family patches, see
TigreGotico/onnx-asr PR #3).
Three-graph layout: encoder.onnx (audio -> projected audio embeddings), embed_tokens.onnx,
and a merged prefill+decode decoder.onnx with a 28-layer KV cache. Prompt token ids are baked
into config.json, so no tokenizer is needed at runtime. fp32 output matches native
transformers character-for-character on FLEURS test clips (en, pt). fp32 and int8 graphs included.
import onnx_asr
model = onnx_asr.load_model("speech-llm", "path/to/this/repo") # or quantization="int8"
print(model.recognize("audio_16khz.wav"))
License: Apache-2.0 (inherited from the source model).
Base model
Qwen/Qwen3-ASR-0.6B-hf