| Property | Value |
|---|---|
| Parameter Count | 559M |
| License | CC-BY-NC-4.0 |
| Paper | View Paper |
| Languages | 94 languages |
| Tensor Type | BF16 |
What is jina-colbert-v2?
Jina-ColBERT V2 is an advanced multilingual late interaction retriever that builds upon its predecessor with significant improvements. It's designed to handle efficient retrieval across 94 languages while maintaining high performance through token-level embeddings and late interaction techniques.
Implementation Details
The model leverages an 8192 token input context and implements Matryoshka embeddings, allowing flexible trade-offs between efficiency and precision. It comes in three variants with different embedding dimensions: 128, 96, and 64, enabling users to choose based on their specific needs.
- Supports 94 languages with strong performance on major global languages
- Features Matryoshka embeddings for efficiency-precision trade-offs
- Implements late interaction for better explainability and performance
- Offers 8192 token input context
Core Capabilities
- Superior retrieval performance compared to previous versions
- Multilingual support with strong performance across languages
- Flexible embedding dimensions for different use cases
- Enhanced efficiency through late interaction architecture
Frequently Asked Questions
Q: What makes this model unique?
The model's combination of multilingual support, Matryoshka embeddings, and late interaction architecture makes it uniquely suited for efficient and accurate retrieval across languages. Its performance consistently exceeds both BM25 and previous ColBERT versions across various benchmarks.
Q: What are the recommended use cases?
The model excels in multilingual passage retrieval, document search, and information retrieval tasks. It's particularly effective for applications requiring cross-lingual search capabilities and those needing flexible performance-efficiency trade-offs.