Instructions to use superb/wav2vec2-base-superb-ks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use superb/wav2vec2-base-superb-ks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="superb/wav2vec2-base-superb-ks")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("superb/wav2vec2-base-superb-ks") model = AutoModelForAudioClassification.from_pretrained("superb/wav2vec2-base-superb-ks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd2b63d93897b3ef937916774517cbb2ed9e03dfdbc4db0318c81f4eb808dbb6
- Size of remote file:
- 378 MB
- SHA256:
- 54b662ca0e56b7581766b0d5afd4cb0828db1740909ef4a89b5b9a5a78d9de33
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