Instructions to use nlpaueb/bert-base-uncased-eurlex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpaueb/bert-base-uncased-eurlex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpaueb/bert-base-uncased-eurlex")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nlpaueb/bert-base-uncased-eurlex", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55a02528c33c3c0d9be10efeee5003fd2f3902a36c93461c1a85a5d2e9239838
- Size of remote file:
- 440 MB
- SHA256:
- 8d0e6bb13c3c2c7818b4163fbcf519d573ac0e9dfb81521bc8954718cc7c5b48
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.