Instructions to use JovialValley/model_syllable_onSet2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JovialValley/model_syllable_onSet2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="JovialValley/model_syllable_onSet2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("JovialValley/model_syllable_onSet2") model = AutoModelForCTC.from_pretrained("JovialValley/model_syllable_onSet2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b9a9dd5d1dc0cdf3ff490d2983e5b071b4a63322155b77a9f9497fb55a4145d
- Size of remote file:
- 1.26 GB
- SHA256:
- 42c2332e444432b9d282f19e557f5fec59dc42ff98558cd7596d9edf303ac150
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