Token Classification
Transformers
Safetensors
Korean
roberta
named-entity-recognition
timex
korean
Eval Results (legacy)
Instructions to use kwoncho/ko-sroberta-korean-time-expression-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kwoncho/ko-sroberta-korean-time-expression-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kwoncho/ko-sroberta-korean-time-expression-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kwoncho/ko-sroberta-korean-time-expression-classifier") model = AutoModelForTokenClassification.from_pretrained("kwoncho/ko-sroberta-korean-time-expression-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ea32c1e344d8d78b4fbbbd3a6708d19b81c78e03997d83dc937903e5d78f0d5
- Size of remote file:
- 5.84 kB
- SHA256:
- fdf542d0e058e1e436f8de44dbf531267f84de401b3bf7b6fe2ba56108bbd3af
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