Instructions to use anderloh/HuggingfaceBest5ClassModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceBest5ClassModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceBest5ClassModel")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceBest5ClassModel") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceBest5ClassModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f71562930c8ef8dafc585e488d7eaef92dd727006849217e0ed3a38916b13937
- Size of remote file:
- 4.98 kB
- SHA256:
- a3218c866c7b253f5d3295edcd44b4197864747f68600a16bb0f3d6f506131fb
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