jina embeddings v5 text : Task Targeted Embedding Distillation Elastic Inference Service ArXiv Release Note Blog Model Overview jina embeddings v5 text nano text matching is a compact, high performance text embedding model designed for text matching. It is part of the jina embeddings v5 text model family, which also includes jina embeddings v5 text small, for better performance at a bigger size. Trained using a novel approach that combines distillation with task specific contrastive losses, jina embeddings v5 text nano text matching outperforms existing state of the art models of similar size across diverse embedding benchmarks. Feature Value Parameters 239M Supported Tasks text matching Max Sequence Length 8192 Embedding Dimension 768 Matryoshka Dimensions 32, 64, 128, 256, 512, 768 Pooling Strategy Last token pooling Base Model jinaai/jina embeddings v5 text nano Training and Evaluation For training details and evaluation results, see our technical report. Usage Requirements The following Python packages are required: transformers =5.1.0 torch =2.8.0 peft =0.15.2 vllm==0.15.1 Optional / Recommended flash attention : Installing flash attention is recommended for improved inference…
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