Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:77455
loss:ContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use EvgenyBondarenko/BIEncoderRanker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use EvgenyBondarenko/BIEncoderRanker with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("EvgenyBondarenko/BIEncoderRanker") sentences = [ "Исследование антигена хеликобактера (Helicobacter pylori)", "Токсоплазма (Toxoplasma gondii): Антитела: IgG, (количественно). Метод: ИФА", "Хеликобактер пилори (Helicobacter pylori): Антитела: IgG, (количественно). Метод: ИФА", "УЗИ молочных желез с эластографией" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle