AI is happening. The future is updating.jina-embeddings-v5-text-nano-retrieval
`jina-embeddings-v5-text-nano-retrieval` is a compact, high-performance text embedding model designed for information retrieval. 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-retrieval` outperforms existing state-of-the-art models of similar size across diverse embedding benchmarks. | Feature | Value | | --- | --- | | Parameters | 239M | | Supported Tasks | `retrieval` | | 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 |
`jina-embeddings-v5-text-nano-retrieval` is a compact, high-performance text embedding model designed for information retrieval. 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-retrieval` outperforms existing state-of-the-art models of similar size across diverse embedding benchmarks. | Feature | Value | | --- | --- | | Parameters | 239M | | Supported Tasks | `retrieval` | | 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 |