Instructions to use EMBO/sd-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBO/sd-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EMBO/sd-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EMBO/sd-ner") model = AutoModelForTokenClassification.from_pretrained("EMBO/sd-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c15f4953c773cbfa77ba856cc5d6aff4f9b2a03e5e8c182d40c3199ddd4c99b
- Size of remote file:
- 496 MB
- SHA256:
- 009f7094e7eba2203b3c3dd3a5f5802bf1593d7e4680934eb55fc5ff8d5371f4
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