Instructions to use SHENMU007/speechcommand-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/speechcommand-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="SHENMU007/speechcommand-demo")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("SHENMU007/speechcommand-demo") model = AutoModelForAudioClassification.from_pretrained("SHENMU007/speechcommand-demo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40976071dc523586b7f07a9d487fdc07baf09c5e300efaddd0a52c99d044bad9
- Size of remote file:
- 378 MB
- SHA256:
- c05b57ce515e291681b0a79c607cc369a5a9d0bd770c2e2a5148e0ab272c7cd3
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