deepvk/USER2-base
sentence-similarity model by deepvk
From the publisher
Model card & documentation
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USER2 is a new generation of the Universal Sentence Encoder for Russian, designed for sentence representation with long-context support of up to 8,192 tokens. The models are built on top of the RuModernBERT encoders and are fine-tuned for retrieval and semantic tasks. They also support Matryoshka Representation Learning (MRL) — a technique that enables reducing embedding size with minimal loss in representation quality. This is a base model with 149 million parameters. To evaluate the model, we measure quality on the MTEB-rus benchmark. Additionally, to measure long-context retrieval, we run Russian subset of MultiLongDocRetrieval (MLDR) task. MTEB-rus MLDR-rus We compare only model with context length of 8192. To evaluate MRL capabilities, we also use MTEB-rus, applying dimensionality cropping to the embeddings to match the selected size. This model is trained similarly to Nomic Embed and expects task-specific prefixes to be added to the input. The choice of prefix depends on…
Read the full model card ↗ · Preview checked 2026-09-26T06:43:47.396Z
Inside the original model card — Document outline
- USER2-base
- Performance
- Matryoshka
- Usage
- Prefixes
- Sentence Transformers
- Transformers
- Training details
- Ablation
- Citations
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
deepvk/USER2-base is a sentence-similarity model repository published by deepvk 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)
- 144,714
- Cumulative likes
- 29
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 149,014,272
- Architecture
- ModernBertModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2025-02-25T11:06:37.000Z
- Last modified
- 2026-03-26T08:40:22.000Z
Compatibility and lineage
Reported languages: ru
Reported base models: deepvk/RuModernBERT-base
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
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-26T06:38:47.548Z. 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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