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
| {"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": false, "special_tokens_map_file": null, "name_or_path": "./v2_evals/checkpoints/T6_noTram2_BERT_norwegian_cased_3.8m", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |