Instructions to use OpenVoiceOS/nvidia-rw-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-rw-conformer-transducer-large-onnx with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("OpenVoiceOS/nvidia-rw-conformer-transducer-large-onnx") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6055b312eca8fe16ca00802a5488a59c46149e9f7fad50d5169d9f4f52f1f51
- Size of remote file:
- 481 MB
- SHA256:
- 86629e18b77e47b46aeb0deb0633cde18da858942c12e99f45d933776258aec4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.