Instructions to use RecordedFuture/Swedish-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RecordedFuture/Swedish-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RecordedFuture/Swedish-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RecordedFuture/Swedish-NER") model = AutoModelForTokenClassification.from_pretrained("RecordedFuture/Swedish-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eeeaef6a51dea0abbf3689a527af0a5b7340f40a19e5772720d7d87feab2e5ad
- Size of remote file:
- 497 MB
- SHA256:
- bfcf6cc4b830ee8270d32186b20240ce1f80a82df954785a235a88f31b2753ed
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