Instructions to use anderloh/HuggingfaceTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceTest")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceTest") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceTest") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68a8292161b47145d4a45ec28ce1cf7ab542ed5847ef63a2c97d53a3f1606532
- Size of remote file:
- 52.2 MB
- SHA256:
- 1cb7f1bd30ddef9fe0e2b0c882bba1509ab7779d208b33616e0f7f05ebd6dbe3
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