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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a01613cdb5c11ad13637eae7f47605dfc9402af98ab2c9d2e58612a6d417c496
- Size of remote file:
- 499 MB
- SHA256:
- fde0c4f917d5ae080cea0c39d803c531620c51ae1220e272c0637d09d70e16be
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