Audio Classification
Transformers
PyTorch
Safetensors
audio-spectrogram-transformer
Eval Results (legacy)
Instructions to use MIT/ast-finetuned-speech-commands-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MIT/ast-finetuned-speech-commands-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="MIT/ast-finetuned-speech-commands-v2")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("MIT/ast-finetuned-speech-commands-v2") model = AutoModelForAudioClassification.from_pretrained("MIT/ast-finetuned-speech-commands-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 499622fc6649403cd93868b798e630e739c3dac5f977da8c59cd50dcd2f419cb
- Size of remote file:
- 342 MB
- SHA256:
- 26cce475c88e1d50bb90ccb5ad6360116a5abf71bbdfddfed8547a435447f5a9
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