Instructions to use SKNahin/NER_YOSO2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SKNahin/NER_YOSO2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SKNahin/NER_YOSO2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SKNahin/NER_YOSO2") model = AutoModelForTokenClassification.from_pretrained("SKNahin/NER_YOSO2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6213cb2e4619e1c9b12f5e5b39d60faddbd7dfcb294900c3d204c10df4f8515e
- Size of remote file:
- 507 MB
- SHA256:
- 5bec1af002df859e70fa0ce785f1383301ef7d3a9ce5bb83b77c599e2db4c66e
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