Instructions to use pratt3000/wav2vec2-base-finetuned-ks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pratt3000/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="pratt3000/wav2vec2-base-finetuned-ks")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("pratt3000/wav2vec2-base-finetuned-ks") model = AutoModelForAudioClassification.from_pretrained("pratt3000/wav2vec2-base-finetuned-ks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b96b36deb5f80064778da36e46c4fb145d4dec348509e49e9309dd08490aada
- Size of remote file:
- 378 MB
- SHA256:
- c2bbaa101f431d2f3fced2e18b66b6343708b0e558ba1d0510356a8f4096ec06
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