Instructions to use AdapterHub/bert-base-uncased-imdb_pfeiffer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use AdapterHub/bert-base-uncased-imdb_pfeiffer with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("bert-base-uncased") model.load_adapter("AdapterHub/bert-base-uncased-imdb_pfeiffer", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_adapter.bin from AdapterHub/bert-base-uncased-imdb_pfeiffer: direct link, hf CLI and curl.
- Browser
- Download file 3.59 MB
-
https://huggingface.co/AdapterHub/bert-base-uncased-imdb_pfeiffer/resolve/main/pytorch_adapter.bin
- Command line
-
hf download hf://AdapterHub/bert-base-uncased-imdb_pfeiffer/pytorch_adapter.bin
-
curl -L -o pytorch_adapter.bin https://huggingface.co/AdapterHub/bert-base-uncased-imdb_pfeiffer/resolve/main/pytorch_adapter.bin
3.59 MB
- Xet hash:
- 60bc1416b4463d1cdd6bf33cf660d2875b7ad0c041d2515cd78a9d56d7e58821
- Size of remote file:
- 3.59 MB
- SHA256:
- 5c582eaf7e1f60e36b6410db3a35f0a4439c9813e62478fccabfca9933da689f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.