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:
- 69a0a37768d9b9b83631d51cd7b209ebc507c0b19b2d0a7e99318473e3483d4b
- Size of remote file:
- 3.06 kB
- SHA256:
- 47800dd08f2ad75f04ac160678e7dffb31b4e03c21fca86a6a9d03cd1764f6cb
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