Instructions to use Masterx/parakeet-tdt-0.6b-v3-fp16-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
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- NeMo
How to use Masterx/parakeet-tdt-0.6b-v3-fp16-onnx with NeMo:
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- Notebooks
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parakeet-tdt-0.6b-v3 โ fp16 ONNX
fp16 conversion of istupakov/parakeet-tdt-0.6b-v3-onnx
(same graph layout: encoder-model + fused decoder_joint-model, .fp16 suffix), made with
onnxruntime's transformers.float16 converter (keep_io_types=True, path-based shape inference
for the >2GB encoder). I/O stays fp32, weights/compute fp16.
Verified vs the fp32 export: random-input parity cos โ 1.0, and END-TO-END transcripts are byte-identical on DirectML while decoding ~2ร faster (66 s clip: 231 ms vs 459 ms warm, RTX 3080 Ti; encoder 92 ms vs 300 ms). Half the download/VRAM of fp32.
Made for WinSTT.
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nvidia/parakeet-tdt-0.6b-v3