Instructions to use superb/wav2vec2-large-superb-sid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use superb/wav2vec2-large-superb-sid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="superb/wav2vec2-large-superb-sid")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("superb/wav2vec2-large-superb-sid") model = AutoModelForAudioClassification.from_pretrained("superb/wav2vec2-large-superb-sid") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f587d50c65eb240dcc66d25dd6d4d99620316f9d9cd83622f3af9352b189a88d
- Size of remote file:
- 1.26 GB
- SHA256:
- a1bbb3a47b40e78d2f7a6a2fece46c341caa224dcbddeaa471c593a718d38a76
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