Instructions to use wldn/korean-text-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wldn/korean-text-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wldn/korean-text-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wldn/korean-text-classification-model") model = AutoModelForSequenceClassification.from_pretrained("wldn/korean-text-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 473 Bytes
87f428b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"base_model": "beomi/KcELECTRA-base",
"task": "text-classification",
"text_column": "text",
"label_column": "label",
"max_length": 128,
"labels": [
"안전",
"의심"
],
"label2id": {
"안전": 0,
"의심": 1
},
"id2label": {
"0": "안전",
"1": "의심"
},
"epochs": 3,
"train_batch_size": 16,
"eval_batch_size": 32,
"learning_rate": 2e-05,
"use_class_weights": true,
"created_at": "2026-06-05T12:10:33.597009"
} |