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:
- 25b7d6c606fed9777828fbca8cc4abc9833bc715207ce6739a12010910c899ea
- Size of remote file:
- 14.2 kB
- SHA256:
- 0524d4c5bb50cb3a888e246202453f6e7f310c8e7d978c2791811f64716d2d2c
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