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Show HN: We built a better reranker and open sourced it
Hi HN,
Our research team just released the best performing and most efficient reranker out there, and it's available now as an open weight model on HuggingFace.
Reranker v2 was designed specifically for agentic RAG, supports instruction following (our v1 was the first to introduce this), and is multilingual.
Along with this, we're also open source our eval set, which allows you to reproduce our benchmark results. By releasing these datasets, we are also advancing instruction-following reranking evaluation, where high-quality benchmarks are currently limited.
Please give it a try and let us know what you think.
- ninalopatina 1y agoOpen weight models: https://huggingface.co/collections/ContextualAI/contextual-ai-reranker-v2-68a60ca62116ac71437b3db7 https://huggingface.co/collections/ContextualAI/contextual-a... Complete eval set: https://huggingface.co/collections/ContextualAI/contextual-ai-instruction-following-retrieval-evals-6899f1dba6d665f884345391 https://huggingface.co/collections/ContextualAI/contextual-a... Blog: https://contextual.ai/blog/rerank-v2/ https://contextual.ai/blog/rerank-v2/
- abhiv91 1y agoThank you for open sourcing! Rerankers are an essential part of a robust RAG app