Instructions to use PaddleCI/tiny-random-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- paddlenlp
How to use PaddleCI/tiny-random-bert with paddlenlp:
from paddlenlp.transformers import AutoTokenizer, BertForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PaddleCI/tiny-random-bert", from_hf_hub=True) model = BertForMaskedLM.from_pretrained("PaddleCI/tiny-random-bert", from_hf_hub=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ec68dfec7a662ecfce4ef382235d190597dab9b68114960874ff91c8c1311af
- Size of remote file:
- 2.1 MB
- SHA256:
- ab2790874db7a25e6555cb4fb6bccb26758b3ea546be1200d9336b5b213bf0ef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.