Instructions to use AdapterHub/bert-base-uncased-pf-fce_error_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use AdapterHub/bert-base-uncased-pf-fce_error_detection with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("bert-base-uncased") model.load_adapter("AdapterHub/bert-base-uncased-pf-fce_error_detection", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model_head.bin from AdapterHub/bert-base-uncased-pf-fce_error_detection: direct link, hf CLI and curl.
- Browser
- Download file 7.22 kB
-
https://huggingface.co/AdapterHub/bert-base-uncased-pf-fce_error_detection/resolve/main/pytorch_model_head.bin
- Command line
-
hf download hf://AdapterHub/bert-base-uncased-pf-fce_error_detection/pytorch_model_head.bin
-
curl -L -o pytorch_model_head.bin https://huggingface.co/AdapterHub/bert-base-uncased-pf-fce_error_detection/resolve/main/pytorch_model_head.bin
7.22 kB
- Xet hash:
- df4643063c09890d9aa087a7a050c9a5445f5102858a9142becfe70fc1b9ea06
- Size of remote file:
- 7.22 kB
- SHA256:
- 86c799a9c69edc8d44014a67f3c77a68e6b28741806880942d68283b33c0dffe
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