Instructions to use OpenVoiceOS/nvidia-en-conformer-transducer-large-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use OpenVoiceOS/nvidia-en-conformer-transducer-large-onnx with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("OpenVoiceOS/nvidia-en-conformer-transducer-large-onnx") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afd837cd8b573793adba0d2f54905a5b1177e8854fe391c8688652ea401a335d
- Size of remote file:
- 21.3 MB
- SHA256:
- e8f9389697c78d08d3ad6c19875f5a2312c52a768ef3c1a7be32a2afb8937c16
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.