Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:19380
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use blemond/0908a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use blemond/0908a with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("blemond/0908a") sentences = [ "query: ASC X.12 는 뭔가요?", "passage: Accredited Standard Committee X.12", "passage: BCP Measurement and statistics Handling", "passage: Bearer Inter Working Function" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K