cointegrated/rubert-tiny2
sentence-similarity model by cointegrated
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Model card & documentation
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This is an updated version of cointegrated/rubert-tiny: a small Russian BERT-based encoder with high-quality sentence embeddings. This post in Russian gives more details. The differences from the previous version include: The model should be used as is to produce sentence embeddings (e.g. for KNN classification of short texts) or fine-tuned for a…
Read the full model card ↗ · Preview checked 2026-10-31T18:54:28.892Z
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Model overview
cointegrated/rubert-tiny2 is a sentence-similarity model repository published by cointegrated on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 367,357
- Cumulative likes
- 184
- Hugging Face trending score
- 1
- Reported safetensors parameters
- 29,378,550
- Architecture
- BertForPreTraining
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2025-12-30T08:33:24.000Z
Compatibility and lineage
Reported languages: ru
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:31.802Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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