Instructions to use Masterx/sherpa-onnx-nemotron-3.5-asr-streaming-0.6b-560ms-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-560ms-2026-06-11 with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
File size: 1,109 Bytes
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license: other
base_model: nvidia/nemotron-3.5-asr-streaming-0.6b
tags:
- onnx
- asr
- streaming
- nemotron
- nemo
- sherpa-onnx
- multilingual
---
# Streaming Nemotron 3.5 ASR (0.6B, multilingual) — 560 ms — sherpa-onnx ONNX
sherpa-onnx streaming transducer export of
[nvidia/nemotron-3.5-asr-streaming-0.6b](https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b)
at the **560 ms** cache-aware chunk (`att_context_size = [56, 6]`), 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](https://github.com/dahshury/WinSTT).
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