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:
- bb0dea19a0cc3bce1834071117cc662b829a63b0ba618a3c1893d5108d1f2f77
- Size of remote file:
- 857 MB
- SHA256:
- ef4c0237a69d1e3194471f7b317ec80bdd20e3aca94a64635838bbe1a413c55e
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