Instructions to use shrdlu9/bert-base-cased-ud-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shrdlu9/bert-base-cased-ud-NER with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForNer tokenizer = AutoTokenizer.from_pretrained("shrdlu9/bert-base-cased-ud-NER") model = BertForNer.from_pretrained("shrdlu9/bert-base-cased-ud-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8deb832a976725cfd761ec8d2c180ad97e4ca71934995c2767d9822d5746115
- Size of remote file:
- 431 MB
- SHA256:
- 79e85c97834863803fa1c10f47742e2cf7d65e0246bf50da67a61cbded1eeba8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.