Instructions to use binwang/RSE-BERT-base-Transfer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/RSE-BERT-base-Transfer with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForRSE tokenizer = AutoTokenizer.from_pretrained("binwang/RSE-BERT-base-Transfer") model = BertForRSE.from_pretrained("binwang/RSE-BERT-base-Transfer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 875021faea7407a61dd62e140f8263bec2a7b75fe0f433eda01dd2bf78e7583c
- Size of remote file:
- 438 MB
- SHA256:
- 53e5296478a5055b50b38a145a796631d7364c0d853bf48681f7b2cc920d255b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.