Instructions to use LucasWeber/id_token_bert_even_LMentry with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LucasWeber/id_token_bert_even_LMentry with Transformers:
# Load model directly from transformers import MultiLabelRaschModel_ID_tokens model = MultiLabelRaschModel_ID_tokens.from_pretrained("LucasWeber/id_token_bert_even_LMentry", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f2493186ef5f84ac42fbc95aba6bed2da48fd19f2671b145eae0b0179377f00
- Size of remote file:
- 441 MB
- SHA256:
- 01694c5963e85276205d6cbd3e024a586117c566521717f574d8e98e8454aaf6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.