Nemotron 3.5 ASR Streaming 0.6B (Multilingual) - ONNX int8
Dynamically int8-quantised ONNX export of nvidia/nemotron-3.5-asr-streaming-0.6b,
laid out for parakeet-rs (>= 0.3.6) and used by Undertone.
A cache-aware streaming FastConformer-RNNT model covering 40 language-locales with native punctuation and capitalisation. The encoder exposes a prompt_index input, so a single graph serves every language; the target language is selected at runtime (or left to auto-detect).
Files
| File | Size | Purpose |
|---|---|---|
encoder.onnx + encoder.onnx.data |
~627 MB | int8 streaming encoder with the prompt-kernel head |
decoder_joint.onnx |
~23 MB | int8 RNNT decoder + joint network |
tokenizer.model |
~0.4 MB | SentencePiece tokenizer (vocab 13088, includes language tags) |
config.json |
~3 KB | streaming params, cache shapes, prompt dictionary |
nemotron-3.5-asr-streaming-0.6b-int8.tar.gz |
~432 MB | the above bundled for Undertone's downloader |
All files must live in the same directory. The parakeet-rs loader auto-detects the multilingual variant by spotting the prompt_index encoder input.
Usage (parakeet-rs)
use parakeet_rs::{Nemotron, NemotronMode};
let mut model = Nemotron::from_pretrained("./nemotron-3.5-asr-streaming-0.6b-int8", None)?;
if model.mode() == NemotronMode::Multilingual {
model.set_target_lang("es-ES")?; // or "auto", "en-US", "ja-JP", "zh-CN", ...
}
// 560ms chunks at 16kHz mono f32
const CHUNK: usize = 8960;
for chunk in audio.chunks(CHUNK) {
print!("{}", model.transcribe_chunk(chunk)?);
}
How this was produced
The two scripts used to produce this repo are included for reproducibility:
export_nemotron_streaming_multilingual.py- NeMo.nemo-> FP32 ONNXquantize_and_package.py- FP32 ONNX -> int8 + tar.gz
Steps:
python export_nemotron_streaming_multilingual.py nemotron-3.5-asr-streaming-0.6b.nemo ./onnx_fp32- exports FP32 ONNX (the encoder's per-languageprompt_indexis exposed as a real ONNX input rather than baked in).python quantize_and_package.py ./onnx_fp32 ./out --tar ./out/nemotron-3.5-asr-streaming-0.6b-int8.tar.gz- quantisesencoder.onnxanddecoder_joint.onnxto int8 viaonnxruntime.quantization.quantize_dynamic(QuantType.QInt8).- Encoder/NeMo parity was verified across en-US, es-ES and ja-JP before quantising (max abs diff < 1e-4).
Input: 16kHz mono f32. Output: text with native punctuation; no word-level timestamps.
Licence and attribution
This is a derivative of NVIDIA's nemotron-3.5-asr-streaming-0.6b, distributed under the OpenMDW 1.1 licence. All model credit belongs to NVIDIA; this repository only re-packages the weights as int8 ONNX.
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