USER2 small USER2 is a new generation of the U niversal S entence E ncoder for R ussian, 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 small model with 34 million parameters. Model Size Context Length Hidden Dim MRL Dims : : : : : : : : : deepvk/USER2 small 34M 8192 384 [32, 64, 128, 256, 384] deepvk/USER2 base 149M 8192 768 [32, 64, 128, 256, 384, 512, 768] Performance 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 Model Size Hidden Dim Context Length MRL support Mean(task) Mean(taskType) Classification Clustering MultiLabelClassification PairClassification Reranking Retrieval STS : : : : : : : : : : : : : : : : : : : : : : : : : : : USER base 124M 768 512 ❌ 58.11 56.67 59.89 53.26 37.72 59.76 55.58 56.14 74.35 USER bge m3 359M 1024 8…
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