Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use heejinoh/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heejinoh/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="heejinoh/ynat-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("heejinoh/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("heejinoh/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from heejinoh/ynat-model: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/heejinoh/ynat-model/resolve/main/training_args.bin
- Command line
-
hf download hf://heejinoh/ynat-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/heejinoh/ynat-model/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 9f231375413254d791713b2c8f7dcc57d46d2774743ab295722159e30511de71
- Size of remote file:
- 5.24 kB
- SHA256:
- 32b86f4dd02d3d4660ab98cf8a5fb75718d00504cd6cfff2012531300b2aa04f
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