Nomic Atlas Retriever
Shares tags: analyze, indexing & search, retrievers
Revolutionize your search capabilities with advanced retrieval technology integrated into Elasticsearch.
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<a href="https://www.stork.ai/en/elastic-learned-sparse-retriever-elsr" target="_blank" rel="noopener noreferrer"><img src="https://www.stork.ai/api/badge/elastic-learned-sparse-retriever-elsr?style=dark" alt="Elastic Learned Sparse Retriever (ELSR) - Featured on Stork.ai" height="36" /></a>
[](https://www.stork.ai/en/elastic-learned-sparse-retriever-elsr)
overview
Elastic Learned Sparse Retriever (ELSR) is a cutting-edge sparse retrieval solution built into Elasticsearch, specifically designed for Retrieval-Augmented Generation (RAG) applications. It combines efficiency with accuracy, empowering organizations to conduct high-relevance searches across various data types and formats.
features
ELSR comes equipped with a suite of features that significantly enhance the search experience. From faster processing speeds to flexible model integration, ELSR meets the needs of diverse user bases.
use cases
ELSR is designed for organizations that prioritize both accuracy and interpretability in search capabilities. From large enterprises to niche startups, ELSR caters to any user looking to leverage advanced retrieval systems effectively.
ELSER v2 features a 60-120% increase in inference speed and enhanced retrieval accuracy due to an expanded training dataset and a refined FLOPS regularizer.
Yes, ELSR is designed with ease of use in mind, featuring a one-click deployment process that allows non-experts to utilize advanced search capabilities without extensive technical knowledge.
Absolutely! ELSR supports external models such as those from Hugging Face, providing users with flexible retrieval options between dense and sparse embeddings.
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For builders
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