Instructions to use AdapterHub/bert-base-multilingual-cased_mlki_tp_pfeiffer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use AdapterHub/bert-base-multilingual-cased_mlki_tp_pfeiffer with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("bert-base-multilingual-cased") model.load_adapter("AdapterHub/bert-base-multilingual-cased_mlki_tp_pfeiffer", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_adapter.bin from AdapterHub/bert-base-multilingual-cased_mlki_tp_pfeiffer: direct link, hf CLI and curl.
- Browser
- Download file 3.59 MB
-
https://huggingface.co/AdapterHub/bert-base-multilingual-cased_mlki_tp_pfeiffer/resolve/main/pytorch_adapter.bin
- Command line
-
hf download hf://AdapterHub/bert-base-multilingual-cased_mlki_tp_pfeiffer/pytorch_adapter.bin
-
curl -L -o pytorch_adapter.bin https://huggingface.co/AdapterHub/bert-base-multilingual-cased_mlki_tp_pfeiffer/resolve/main/pytorch_adapter.bin
3.59 MB
- Xet hash:
- 61d699dcc99d301bd4086bfcd57d1c80c6e1b918ef3c8bae1dc4cb7cd1a57e62
- Size of remote file:
- 3.59 MB
- SHA256:
- 2124f73caed0fdb8f63f63b7d7c7bd362671279146c4540b1af193ebe5a44989
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.