README.md

---
language:
- ru
library_name: sentence-transformers
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- static-embeddings
- binary
- russian
---

# StaRSE-512

**StaRSE** stands for **Sta**tic **R**ussian **S**entence **E**mbeddings. It is a compact Russian sentence embedding model implemented as a
[Sentence-Transformers](https://www.sbert.net/) `StaticEmbedding`
endpoint.

The model is intended for CPU-friendly semantic similarity, clustering,
classification features, and retrieval-style first-stage representations when a
full Transformer encoder is too expensive to run at high throughput.

![RuMTEB quality-latency trade-off](assets/rumteb_cpu_latency.png)

## Performance

Evaluation is reported on
[`MTEB(rus, v1.1)`](https://docs.mteb.org/overview/available_benchmarks/#mtebrus-v11)
across 23 tasks. The main score is `mean_task_main_score = 51.16`.

| Task type | Tasks | Mean score |
|---|---:|---:|
| Classification | 9 | 56.81 |
| Clustering | 3 | 51.80 |
| MultilabelClassification | 2 | 35.01 |
| PairClassification | 1 | 52.50 |
| Reranking | 2 | 41.88 |
| Retrieval | 3 | 39.09 |
| STS | 3 | 62.18 |

## Usage

Install [Sentence Transformers](https://www.sbert.net/docs/installation.html):

```bash
pip install -U sentence-transformers
```

Load the model with `trust_remote_code=True`.

```python
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("BorisTM/starse-512", trust_remote_code=True)

sentences = [
    "Партитуры Чайковского часто звучат в консерватории.",
    "Балетная сцена хранит музыку Щелкунчика.",
    "Футбольная команда выиграла матч.",
]

embeddings = model.encode(sentences, normalize_embeddings=True)
similarities = model.similarity(embeddings, embeddings)
print(embeddings.shape)           # (3, 512)
print(tuple(similarities.shape))  # (3, 3)
print(similarities)
# tensor([[1.0000, 0.3521, 0.0626],
#         [0.3521, 1.0000, 0.0420],
#         [0.0626, 0.0420, 1.0000]])
```


## Citation

```bibtex
@misc{starse2026,
  title = {TBD},
  author = {TBD},
  year = {TBD},
  url = {https://huggingface.co/BorisTM/starse-512}
}
```