Text Ranking
sentence-transformers
Safetensors
Russian
English
modernbert
sentence-similarity
feature-extraction
dense
Generated from Trainer
dataset_size:7211755
loss:MatryoshkaLoss
loss:CachedMultipleNegativesRankingLoss
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use fyaronskiy/code_retriever_ru_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use fyaronskiy/code_retriever_ru_en with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("fyaronskiy/code_retriever_ru_en") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle