Instructions to use EMBO/sd-ner-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBO/sd-ner-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EMBO/sd-ner-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EMBO/sd-ner-v2") model = AutoModelForTokenClassification.from_pretrained("EMBO/sd-ner-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29e2153ebca1f23043ea1a5d3bf7095a656d04c10df6d656098571fce4a5c342
- Size of remote file:
- 436 MB
- SHA256:
- 6c684c40f366ffcd2dd771ecd099ccd15bf81d0b633ffaee1695acb47a79935a
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