Sentence Similarity
sentence-transformers
Safetensors
Korean
modernbert
feature-extraction
Generated from Trainer
dataset_size:1120235
loss:CachedMultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use sigridjineth/ModernBERT-korean-large-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sigridjineth/ModernBERT-korean-large-preview with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sigridjineth/ModernBERT-korean-large-preview") sentences = [ "나, 가스불, 찻물, 올리다", "나는 가스불에 꽃을 넣은 찻물을 올렸다.", "과제수행 기간중에 연구 현장에 대해 정기점검을 실시하고, 과제 수행 종료 후에도 일정한 안전조치를 이행하도록 규정한다.", "고기, 상추, 밥, 나, 올리다" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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