Instructions to use Masterx/canary-1b-flash-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Masterx/canary-1b-flash-onnx with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("Masterx/canary-1b-flash-onnx") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5ab7a0dcd08d591769665643ddcd508b5159707932c4339aa9b5b25e6197b76
- Size of remote file:
- 3.28 GB
- SHA256:
- 2c3b11637857564220e28f5b57037c78e4234e550e980cdd5b91c9b18ba2a887
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