Instructions to use NCAI/NCAI-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NCAI/NCAI-BERT with Transformers:
# Load model directly from transformers import LeanAlbertForPretraining model = LeanAlbertForPretraining.from_pretrained("NCAI/NCAI-BERT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29091eb3d004dfe2c4d88687cff7e1660ce98b10becc0d7871b75a5bafe47388
- Size of remote file:
- 734 MB
- SHA256:
- 7a0c93e0b729af8d029f2d02baa617508ed30dddc3e1cb1b944673728f1be32c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.