Text Classification
Transformers
Safetensors
Korean
electra
korean_NLP
KoELECTRA
Generated from Trainer
Instructions to use yaongua/ynat_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yaongua/ynat_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yaongua/ynat_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yaongua/ynat_model") model = AutoModelForSequenceClassification.from_pretrained("yaongua/ynat_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 707fd5dc5c06d23b953b45483c442cdbcba0fc1de63bcb0ec20534a3b8d56947
- Size of remote file:
- 5.78 kB
- SHA256:
- ad24c7baa7c0690bc1643afd3b468e40569555e895d1968fcab1a3a3c2604c82
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