Instructions to use microsoft/wavlm-base-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/wavlm-base-plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/wavlm-base-plus")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/wavlm-base-plus") model = AutoModel.from_pretrained("microsoft/wavlm-base-plus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5b9621d4d9d10b438f0f0024efd6972e276b3a02da493113be3afb200ddbb0e
- Size of remote file:
- 378 MB
- SHA256:
- 3bb273a6ace99408b50cfc81afdbb7ef2de02da2eab0234e18db608ce692fe51
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