Instructions to use flax-community/hubert-dementia-screening with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/hubert-dementia-screening with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="flax-community/hubert-dementia-screening")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("flax-community/hubert-dementia-screening") model = AutoModel.from_pretrained("flax-community/hubert-dementia-screening") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a18e75bdd4217f4881e3149413c447824ff610a83fa53a5691daf9e977783f00
- Size of remote file:
- 418 MB
- SHA256:
- d9182ceb19f342e64595b56f8cefbe3aad87fc906c46824798741c3221f55956
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