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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec1babf7d4f130bd9d1fbf419fe8166f60ad964f6ce640c50a7eead71e396735
- Size of remote file:
- 495 MB
- SHA256:
- 84cddd8816b2b283cf0af942b4a79331313b6f986ac9eb8425557cf2d270e7d2
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