SKTBrain/KoBERT
Korean BERT pre-trained cased (KoBERT) observed · 2026-08-28
Health v2 · maintenance only
44/100
- Activity 26
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2536
- days_rel: n/a
- days_push: 445
- n_releases_24m: 0
Adoption not part of the score
1416 stars · 377 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
KoBERT is a Korean BERT language model pre-trained on Korean Wikipedia by SK Telecom, distributed as a Python package with PyTorch, ONNX, and MXNet/Gluon interfaces plus a SentencePiece tokenizer. It also provides subtask models such as Naver sentiment analysis, Korean NER with CRF, and Korean Sentence BERT.
Use cases
- fine-tune BERT on Korean text
- Korean sentiment analysis
- Korean named entity recognition
- generate Korean sentence embeddings
- use a Korean language model in PyTorch or ONNX
When to choose
- you need a compact, well-tested Korean BERT encoder for classification, NER, or embeddings
- you work in PyTorch or Hugging Face transformers and want Korean pretraining
When to avoid
- you need a multilingual or newest-generation Korean model with larger vocabulary
- you need active feature development rather than a maintained pretrained model
Facets
library · maturity maintenance
machine-learning nlp transformers machine-learning deep-learning python korean-nlp bert language-model pytorch sentencepiece pretrained-model natural-language-processing gpu
1 source
- readme: https://github.com/SKTBrain/KoBERT · fetched 2026-08-28 · bb156b115aef
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| SKTBrain/KoBERT | main | 44 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem