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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from flax-community/hubert-dementia-screening: direct link, hf CLI and curl.
- Browser
- Download file 418 MB
-
https://huggingface.co/flax-community/hubert-dementia-screening/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://flax-community/hubert-dementia-screening/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/flax-community/hubert-dementia-screening/resolve/main/flax_model.msgpack
418 MB
- Xet hash:
- a18e75bdd4217f4881e3149413c447824ff610a83fa53a5691daf9e977783f00
- Size of remote file:
- 418 MB
- SHA256:
- d9182ceb19f342e64595b56f8cefbe3aad87fc906c46824798741c3221f55956
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