Russian sentence embeddings
According to the model card, it is a fast BERT model for Russian sentence-embedding calculation.
Open Source Model Profile · sergeyzh
rubert-tiny-turbo
rubert-tiny-turbo is a 29.2M-parameter BERT-family Russian sentence-embedding model from sergeyzh. The model card describes it as based on cointegrated/rubert-tiny2.
- Publisher
- sergeyzh
- Task
- sentence-similarity
- Model type
- bert
- License
- mit
- Library
- sentence-transformers
- Publication status
- Accepted · not indexed
Model overview
rubert-tiny-turbo is published by sergeyzh as a sentence-similarity model. The captured configuration identifies BertModel with a bert model type and Safetensors metadata reports 29193768 parameters. According to the model card, it is a fast Russian sentence-embedding BERT model based on cointegrated/rubert-tiny2.
Recorded capabilities
rubert-tiny2 lineage
The model card says it is based on cointegrated/rubert-tiny2, and hub tags record that base model.
Compact 312-dimension output
According to the model card, it keeps 2048 context with 312 embedding size and similar speed to the base model.
Sentence-Transformers use
The model card documents use with SentenceTransformer and util, including loading sergeyzh/rubert-tiny-turbo by name.
Use cases in the source record
- Russian sentence-embedding workflows with the documented SentenceTransformer loading and encoding example.
- According to the model card, embedding comparison settings covered by the publisher-reported encodechka benchmark table.
Limitations and unknowns
- No independent Ethen evaluation results were extracted; benchmark figures come from the publisher model card.
- No context-window value was separately extracted beyond the card-reported 2048 context size.
- Provider state is historical snapshot data, not independently refreshed current availability.
- Training, language coverage, and metric details come from the publisher model card and have not been independently verified by Ethen.
Source and provenance
Source: sergeyzh/rubert-tiny-turbo
Captured: Unknown. Processed: 2026-09-07T19:34:58.887647+00:00.
Быстрая модель BERT для расчетов эмбеддингов предложений на русском языке. Модель основана на cointegrated/rubert-tiny2 - имеет аналогичные размеры контекста (2048), ембеддинга (312) и быстродействие. Использование from sentence_transformers import SentenceTransformer, util model = SentenceTransformer( 'sergeyzh/rubert-tiny-turbo' ) sentences = [ "привет мир" , "hello world" , "здравствуй вселенная" ] embeddings = model.encode(sentences) print (util.dot_score(embeddings, embeddings)) Метрики Оценки модели на бенчмарке encodechka : model CPU GPU size Mean S Mean S+W dim sergeyzh/LaBSE-ru-turbo 120.40 8.05 490 0.789 0.702 768 BAAI/bge…
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