Instructions to use universalml/CA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalml/CA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="universalml/CA")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("universalml/CA") model = AutoModelForAudioClassification.from_pretrained("universalml/CA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0378b3ccec102e041702bb3e373ef4992c0490c9315ab427952d33499b96c6f
- Size of remote file:
- 4.09 kB
- SHA256:
- a7e6b255fef36198af3be1cc8cb2b57309e6d39acd74f319c81946f581b3e45f
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