Automatic Speech Recognition
NeMo
ONNX
Safetensors
GGUF
parakeet_tdt
parakeet
tdt
sherpa-onnx
multilingual
speech-recognition
gabor
fastconformer
Instructions to use oruk/orukeet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use oruk/orukeet with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("oruk/orukeet") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Commit History
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Add qualified Transformers FP32 export for standard Parakeet clients
Verified signatureStrict mapping of all723 source tensors; reproducible conversion; actual Buzz offline/multilingual checks;120-clip export comparison reports5.43% vs source-NeMo5.34% WER separately from published model benchmark. Existing artifacts and metadata preserved.10b603f