monologg/KoELECTRA
A Korean ELECTRA language model trained on 34GB of Korean text, available in base and small variants.
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KoELECTRA is a pretrained ELECTRA-based language model specifically designed for Korean language processing. It uses replaced token detection training, which provides learning signals from all input tokens rather than just masked positions. The model comes in base and small variants, supports both PyTorch and TensorFlow frameworks, and integrates with the Hugging Face Transformers library for easy loading and inference.
Frequently asked
- What is monologg/KoELECTRA?
- A Korean ELECTRA language model trained on 34GB of Korean text, available in base and small variants.
- Is KoELECTRA open source?
- Yes — monologg/KoELECTRA is open source, released under the Apache-2.0 license.
- What language is KoELECTRA written in?
- monologg/KoELECTRA is primarily written in Python.
- How popular is KoELECTRA?
- monologg/KoELECTRA has 637 stars on GitHub.
- Where can I find KoELECTRA?
- monologg/KoELECTRA is on GitHub at https://github.com/monologg/KoELECTRA.