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:
- 40f2841c6d5c3e1ce1032eec9c1e3856fe9e9b4cda5e8e29c04ae9c86e685c2e
- Size of remote file:
- 3.63 kB
- SHA256:
- 0d47e25537d0fc9f714d811aca175778c3518388d9e47e4170cecb31fc2aff92
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