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:
- f27c6fd7c2b23c7d4cca62068a13b2812989cda52a6de0424cd1f695f3cfa326
- Size of remote file:
- 316 MB
- SHA256:
- b786c1275dc452bde873792ce0742aadc04a34b5a0a9d7a8188872efc838d90d
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