“Learn about Cohere reranking, how to use Cohere's Rerank 3 model with the Elasticsearch open inference API and Elastic's roadmap for semantic reranking.”

Elastic’s approach to hybrid search

Cohere’s approach to reranking

Building a RAG implementation with Elasticsearch and Cohere

Elasticsearch vector database

Cohere reranking

Elasticsearch’s accelerated roadmap to semantic reranking and retrievers

Cohere’s generative model capabilities

Rerankers take the ‘top n’ search results from existing vector search and keyword search systems, and provide a semantic boost to those results.

What are rerankers?

Cohere’s Rerank 3 model integration with Elasticsearch

Elasticsearch open Inference API adds support for Cohere’s Rerank 3 model

Elasticsearch open inference API extends support for models from Hugging Face, and brings native chunking to Hugging Face users

Disambiguation

What is the Elasticsearch open inference API?

What is the Hugging Face Inference Endpoint service?

How to use Hugging Face Inference Endpoints with the Elasticsearch open inference API

Step 1: Create an Inference Endpoint service in Hugging Face

Step 2: Create an Inference Endpoint object in Elasticsearch

Step 3: Perform inference using the Inference Endpoint object to access your Hugging Face inference endpoint service

Step 4: Ingest your dataset into an index with semantic text

Step 5: Perform semantic search with semantic text

Step 6: Rerank with Cohere to get even better results

Use Hugging Face Inference Endpoints service with Elastic today!

Elasticsearch open inference API adds native chunking support for Hugging Face

Author

Max Hniebergall

Articles

Elasticsearch open Inference API adds support for Cohere’s Rerank 3 model

Elasticsearch open inference API adds native chunking support for Hugging Face