Instructions to use KBLab/bert-base-swedish-cased-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBLab/bert-base-swedish-cased-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KBLab/bert-base-swedish-cased-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KBLab/bert-base-swedish-cased-ner") model = AutoModelForTokenClassification.from_pretrained("KBLab/bert-base-swedish-cased-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9ba93d92bcb52b000b615f97fe6c88d88108df05e982eb4e723cea1548411c3
- Size of remote file:
- 499 MB
- SHA256:
- 7e8ad48a821068c43cd7d4b9d051f2eeb3cad08b5f0f7f7377bb3f3791a53a14
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