Instructions to use facebook/hubert-xlarge-ll60k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/hubert-xlarge-ll60k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/hubert-xlarge-ll60k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("facebook/hubert-xlarge-ll60k") model = AutoModel.from_pretrained("facebook/hubert-xlarge-ll60k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d47d530e959623f2b28feb9e8c6d520a2c1017249e40fb88fca82e8a84a8572f
- Size of remote file:
- 3.85 GB
- SHA256:
- 6131dc27f4508595daa1a13fec4aa1f6b4a579b5d93550bae26c13a83221f8a7
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