Text Classification
Transformers
Safetensors
Korean
electra
text_classification
korean_NLP
koELECTRA
Generated from Trainer
Instructions to use imha123/ynat_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imha123/ynat_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="imha123/ynat_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("imha123/ynat_model") model = AutoModelForSequenceClassification.from_pretrained("imha123/ynat_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4962b8d3129c633045e4590bafbb0474c22089c0b4718973780eb1eb3aa93fa2
- Size of remote file:
- 5.78 kB
- SHA256:
- 7dc8a067e9ed088fa1ea9c06d5967fb5f54729319faf160c17e986442572d6ed
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