Instructions to use facebook/hubert-large-ll60k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/hubert-large-ll60k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/hubert-large-ll60k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("facebook/hubert-large-ll60k") model = AutoModel.from_pretrained("facebook/hubert-large-ll60k") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3604267c8be8be5ee18246c3cc8512aa5310802b3f2214ca05ce4cfa321d612e
- Size of remote file:
- 1.26 GB
- SHA256:
- 45a299050945479a68cffe2ab7a63fd08931718ba18f05a42dbb86a5164178e0
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