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Amazon Sagemaker

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

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[DEP] Cohere Rerank 3 Model - English Free trial

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Rerank will return a sorted list of documents based on the semantic similarity between the query and documents.
  • This product has been removed and is no longer available to new customers.

Product Overview

This listing is deprecated. Please subscribe to the new Rerank 3 listing in the marketplace. Cohere's Rerank endpoint enables you to significantly improve search quality by augmenting traditional key-word based search systems with a semantic-based reranking system which can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers much higher quality results than just embedding-based search, and it requires only adding a single line of code into your application.

Key Data

Type
Model Package
Fulfillment Methods
Amazon SageMaker

Highlights

  • Cohere's Rerank endpoint can be applied to both keyword-based search systems and vector search systems. When using a keyword-based search engine, like Elasticsearch or OpenSearch, the Rerank endpoint can be added to the end of an existing search workflow and will allow users to incorporate semantic relevance into their keyword search system without changing their existing infrastructure. This is an easy and low-complexity method of improving search results by introducing semantic search technology into a user’s stack.

  • This endpoint is powered by our large language model that computes a score for the relevance of the query with each of the initial search results. Compared to embedding-based semantic search, it yields better search results — especially for complex and domain-specific queries.

  • Rerank supports JSON objects as documents where users can specify at query time the fields (keys) that semantic search should be applied over.

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Usage Information

Model input and output details

Input

Summary

The model accepts JSON requests that specifies the input objects to be reranked - the user can specify this at which keys to be reranked by adjusting the rank_fields parameter. Alternatively, the user can just send a list of texts to be reranked.

Input MIME type
application/json
Sample input data

Output

Summary

The output is a JSON object of reranked results:

{ "id": "57cc4b9b-f4a1-4e0a-830f-40cfc76c0ba6", "results": [ { "document": { "text": "Washington, DC es la capital de los Estados Unidos." }, "index": 3, "relevance_score": 0.9871293 }, { "document": { "text": "उत्तरी मारियाना द्वीप समूह का राष्ट्रमंडल प्रशांत महासागर में द्वीपों का एक समूह है।" }, "index": 1, "relevance_score": 0.29961726 } ], }

Output MIME type
application/json
Sample output data

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Support Information

[DEP] Cohere Rerank 3 Model - English

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Refund Policy

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