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:
- 7b5f22bf29ff7464c2e31ae64b1760eb18a9c2a097b5619000c59912baa3841f
- Size of remote file:
- 3.9 kB
- SHA256:
- 0e2a979d227c4dfbe49590c0ea4a168debe6309d8d86d5f023d6df9924a69c71
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