Instructions to use AdapterHub/bert-base-uncased-pf-record with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use AdapterHub/bert-base-uncased-pf-record with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("bert-base-uncased") model.load_adapter("AdapterHub/bert-base-uncased-pf-record", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_adapter.bin from AdapterHub/bert-base-uncased-pf-record: direct link, hf CLI and curl.
- Browser
- Download file 3.6 MB
-
https://huggingface.co/AdapterHub/bert-base-uncased-pf-record/resolve/main/pytorch_adapter.bin
- Command line
-
hf download hf://AdapterHub/bert-base-uncased-pf-record/pytorch_adapter.bin
-
curl -L -o pytorch_adapter.bin https://huggingface.co/AdapterHub/bert-base-uncased-pf-record/resolve/main/pytorch_adapter.bin
3.6 MB
- Xet hash:
- 28d89774e87a09180f04eabe820b98f7f3dc7cdd896da5ca880efaa4a5c78dcb
- Size of remote file:
- 3.6 MB
- SHA256:
- 9c9a55240a6a1cac6de1fbda8f2f8951c00e8d6efa4e82038fea697256ef69f1
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