Instructions to use AdapterHub/bert-base-uncased-pf-swag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use AdapterHub/bert-base-uncased-pf-swag with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("bert-base-uncased") model.load_adapter("AdapterHub/bert-base-uncased-pf-swag", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_adapter.bin from AdapterHub/bert-base-uncased-pf-swag: direct link, hf CLI and curl.
- Browser
- Download file 3.59 MB
-
https://huggingface.co/AdapterHub/bert-base-uncased-pf-swag/resolve/main/pytorch_adapter.bin
- Command line
-
hf download hf://AdapterHub/bert-base-uncased-pf-swag/pytorch_adapter.bin
-
curl -L -o pytorch_adapter.bin https://huggingface.co/AdapterHub/bert-base-uncased-pf-swag/resolve/main/pytorch_adapter.bin
3.59 MB
- Xet hash:
- 81abfad0a851aa7c3e2fdd623fd6a09d8597e6df1892e8a9832035c8805952d6
- Size of remote file:
- 3.59 MB
- SHA256:
- d74d560a158ce4981f7f00370055d86a1dc998440d7e80d8b19cdbd6a7a35f3b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.