Instructions to use Sharpaxis/BERT-NER-CoNLL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/BERT-NER-CoNLL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Sharpaxis/BERT-NER-CoNLL")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/BERT-NER-CoNLL") model = AutoModelForTokenClassification.from_pretrained("Sharpaxis/BERT-NER-CoNLL") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef9edfad10b8353e3edc772d8657a90cdca431a3a7908835d35cf6a36fe3d4a4
- Size of remote file:
- 5.3 kB
- SHA256:
- bf84e8883f819e3240a70099bae79380c0c9354c43f19e50c5066e4f8a1081f0
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