Instructions to use alg166/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alg166/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="alg166/checkpoints")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("alg166/checkpoints") model = AutoModelForAudioClassification.from_pretrained("alg166/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbbbb08db465eb80b10f015309dee771f7dd38d69ea150304c7f45596e10cf42
- Size of remote file:
- 5.14 kB
- SHA256:
- cee928b85849ac57683afbc1e27296844ad17f1fca2eafb472b12863cd300c82
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