Instructions to use hf-internal-testing/tiny-random-BertForNextSentencePrediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForNextSentencePrediction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForNextSentencePrediction") model = AutoModelForNextSentencePrediction.from_pretrained("hf-internal-testing/tiny-random-BertForNextSentencePrediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- baeaf5fa82abcb61c3c4d6a8d4d888531767e4e00dc82b99dde68f479b151bf9
- Size of remote file:
- 481 kB
- SHA256:
- a3bd8b5b8e51a4f1f210ca90b2e12c046033511433d820fe9ea83f4f338aee63
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.