Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use sungsy0323/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sungsy0323/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sungsy0323/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sungsy0323/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("sungsy0323/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sungsy0323/ynat-model: direct link, hf CLI and curl.
- Browser
- Download file 815 kB
-
https://huggingface.co/sungsy0323/ynat-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://sungsy0323/ynat-model/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/sungsy0323/ynat-model/resolve/main/tokenizer.json
815 kB
File too large to display, you can check the raw version instead.