Instructions to use microsoft/wavlm-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/wavlm-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/wavlm-large")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/wavlm-large") model = AutoModel.from_pretrained("microsoft/wavlm-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6995f3af077c22b165f83242a3c217f6d1864442182e5a4cf6546c39e48bc5df
- Size of remote file:
- 1.26 GB
- SHA256:
- fdee460e529396ddb2f8c8e8ce0ad74cfb747b726bc6f612e666c7c1e1963c9d
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