Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use ssanna/ynat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssanna/ynat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ssanna/ynat")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ssanna/ynat") model = AutoModelForSequenceClassification.from_pretrained("ssanna/ynat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ssanna/ynat: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/ssanna/ynat/resolve/main/training_args.bin
- Command line
-
hf download hf://ssanna/ynat/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/ssanna/ynat/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 605a73d335055f06bf1a3b114e1f1e118747b73dfa5d0b127e31b947e8c78f18
- Size of remote file:
- 5.3 kB
- SHA256:
- f91bc6d2fef9066fae5fdca2c8ebf7f04b00b0b9681cb9ee5da8c4da31d97d01
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