Instructions to use anderloh/testModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/testModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/testModel")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/testModel") model = AutoModelForAudioClassification.from_pretrained("anderloh/testModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 286456c91f69e1d4493e128eab8c2d4ac42204db5ec8c8d99dce9f86d34afd7c
- Size of remote file:
- 95.9 MB
- SHA256:
- a38ed100248348a22bbe356bdb7ab0ec11e07281896386c8e5020aff7a513edb
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