Instructions to use microsoft/wavlm-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/wavlm-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/wavlm-base")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/wavlm-base") model = AutoModel.from_pretrained("microsoft/wavlm-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f99302e8227c70b54cc1c2db44b89d566fddfb151b512cabc9a25e6f66c2c73
- Size of remote file:
- 378 MB
- SHA256:
- b41ab60fdcdc113ff164212c72b371dcd420a5773ca1f6c8f54d6809225ce072
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