jina-reranker-v2-base-multilingual EU AI Act Compliance Profile

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jina-reranker-v2-base-multilingual

Intended Usage & Model Info

The Jina Reranker v2 (jina-reranker-v2-base-multilingual) is a transformer-based model that has been fine-tuned for text reranking task, which is a crucial component in many information retrieval systems. It is a cross-encoder model that takes a query and a document pair as input and outputs a score indicating the relevance of the document to the query. The model is trained on a large dataset of query-document pairs and is capable of reranking documents in multiple languages with high accuracy.

Compared with the state-of-the-art reranker models, including the previous released jina-reranker-v1-base-en, the Jina Reranker v2 model has demonstrated competitiveness across a series of benchmarks targeting for text retrieval, multilingual capability, function-calling-aware and text-to-SQL-aware reranking, and code retrieval tasks.

The jina-reranker-v2-base-multilingual model is capable of handling long texts with a context length of up to 1024 tokens, enabling the processing of extensive inputs. To enable the model to handle long texts that exceed 1024 tokens, the model uses a sliding window approach to chunk the input text into smaller pieces and rerank each chunk separately.

The model is also equipped with a flash attention mechanism, which significantly improves the model's performance.

Usage

This model repository is licenced for research and evaluation purposes under CC-BY-NC-4.0. For commercial usage, please refer to Jina AI's APIs, AWS Sagemaker or Azure Marketplace offerings. Please contact us for any further clarifications.

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