Instructions to use universalml/test27 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalml/test27 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="universalml/test27")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("universalml/test27") model = AutoModelForAudioClassification.from_pretrained("universalml/test27", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 806980e11849d07fa6fbdde522b277e42c666df8ef05ef49c7f0b37b8d0de29f
- Size of remote file:
- 378 MB
- SHA256:
- 135bf94842d3abe2a4e767f2d95f2ef3bb36c47f89be195582356d4ea2529773
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