provenance/README.upstream.md

metadata

license: cc-by-4.0
language:
  - en
  - es
  - fr
  - de
  - bg
  - hr
  - cs
  - da
  - nl
  - et
  - fi
  - el
  - hu
  - it
  - lv
  - lt
  - mt
  - pl
  - pt
  - ro
  - sk
  - sl
  - sv
  - ru
  - uk
base_model:
  - nvidia/parakeet-tdt-0.6b-v3
pipeline_tag: automatic-speech-recognition
tags:
  - automatic-speech-recognition
  - asr
  - onnx
  - onnx-asr

NVIDIA Parakeet TDT 0.6B V3 (Multilingual) model converted to ONNX format for onnx-asr.

Install onnx-asr

pip install onnx-asr[cpu,hub]

Load Parakeet TDT model and recognize wav file

import onnx_asr
model = onnx_asr.load_model("nemo-parakeet-tdt-0.6b-v3")
print(model.recognize("test.wav"))

Code for models export

import nemo.collections.asr as nemo_asr
from pathlib import Path

model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-tdt-0.6b-v3")

onnx_dir = Path("nemo-onnx")
onnx_dir.mkdir(exist_ok=True)
model.export(str(Path(onnx_dir, "model.onnx")))

with Path(onnx_dir, "vocab.txt").open("wt") as f:
    for i, token in enumerate([*model.tokenizer.vocab, "<blk>"]):
        f.write(f"{token} {i}\n")