Text Classification
Transformers
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use bongbongbong/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bongbongbong/tmp_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bongbongbong/tmp_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bongbongbong/tmp_trainer") model = AutoModelForSequenceClassification.from_pretrained("bongbongbong/tmp_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdcdc2119ff3cad8b9f1d4dcde8638f3b1f3bb8778b7c9719be645ec5307841d
- Size of remote file:
- 5.37 kB
- SHA256:
- e65c4aa8b7b20446eb8c3449f43d15c4b13a8ba03dd29bf829b12ccf440eda2e
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