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
File size: 374 Bytes
7d773c6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"label_to_id": {
"O": 0,
"B-DATE": 1,
"I-DATE": 2,
"B-TIME": 3,
"I-TIME": 4,
"B-DURATION": 5,
"I-DURATION": 6,
"B-SET": 7,
"I-SET": 8
},
"id_to_label": {
"0": "O",
"1": "B-DATE",
"2": "I-DATE",
"3": "B-TIME",
"4": "I-TIME",
"5": "B-DURATION",
"6": "I-DURATION",
"7": "B-SET",
"8": "I-SET"
}
} |