Text Classification
Transformers
Safetensors
Korean
electra
korean_NLP
koELECTRA
Generated from Trainer
Instructions to use raaami/ynat_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raaami/ynat_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raaami/ynat_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("raaami/ynat_model") model = AutoModelForSequenceClassification.from_pretrained("raaami/ynat_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 541b9cf021b0927c17c4da1d116d4aaf203c09cf9aba131d5da2f3effd676a08
- Size of remote file:
- 5.78 kB
- SHA256:
- c77581dd6eaa06d19cc5de16848769594fbcfcaac9c8e609a895bd7d5cbf7aeb
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