Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use LeaMac/final_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeaMac/final_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="LeaMac/final_model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("LeaMac/final_model") model = AutoModelForAudioClassification.from_pretrained("LeaMac/final_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6423e5d00d94c942cdfaa9d819c78d7b9247a7e14d912f72a8f0ef7de1d186c1
- Size of remote file:
- 5.37 kB
- SHA256:
- ce0eaffb95fc4e3258fbe23f869892d5430343ddb7c49ad8d61e8d1de3137a7b
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