Instructions to use Masterx/sherpa-onnx-nemotron-3.5-asr-streaming-0.6b-320ms-2026-06-11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Masterx/sherpa-onnx-nemotron-3.5-asr-streaming-0.6b-320ms-2026-06-11 with NeMo:
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- Notebooks
- Google Colab
- Kaggle
Streaming Nemotron 3.5 ASR (0.6B, multilingual) β 320 ms β sherpa-onnx ONNX
sherpa-onnx streaming transducer export of
nvidia/nemotron-3.5-asr-streaming-0.6b
at the 320 ms cache-aware chunk (att_context_size = [56, 3]), produced with
sherpa-onnx's official scripts/nemo/nemotron-3.5-asr-streaming-0.6b/export_onnx.py.
Ships the full package:
- fp32:
encoder.onnx+encoder.data,decoder.onnx,joiner.onnx - int8:
encoder.int8.onnx,decoder.int8.onnx,joiner.int8.onnx(ORT dynamic) - fp16:
encoder.fp16.onnx,decoder.fp16.onnx,joiner.fp16.onnx(onnxruntime float16,keep_io_types) tokens.txt
The multilingual prompt_index encoder input is exposed for per-stream language selection
(or auto = the metadata auto_prompt_id). Sibling of the -1120ms export.
Made for WinSTT.
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nvidia/nemotron-3.5-asr-streaming-0.6b