Instructions to use NbAiLab/nb-bert-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-bert-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="NbAiLab/nb-bert-base-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-bert-base-ner") model = AutoModelForTokenClassification.from_pretrained("NbAiLab/nb-bert-base-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 326f13551446a31fd7d4938da2a48f46fe072d99b1bff75cebc576e02867de31
- Size of remote file:
- 496 MB
- SHA256:
- 25de6239b8ba88a29e39b7b1fa1c3b604b81ed8bfa634554f53f4b5bcbb3493e
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