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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Cohere Multilingual Embedding Model
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Latest Version:
v2.0.1
Use Cohere's multilingual embedding model to map text to a semantic vector space, positioning text with a similar meaning in close proximity
Product Overview
At Cohere, we are committed to breaking down barriers and expanding access to cutting-edge NLP technologies that power projects across the globe. By making our innovative multilingual language models available to all developers, we continue to move toward our goal of empowering developers, researchers, and innovators with state-of-the-art NLP technologies that push the boundaries of Language AI. Our Multilingual Model maps text to a semantic vector space, positioning text with a similar meaning in close proximity. This process unlocks a range of valuable use cases for multilingual settings. For example, one can map a query to this vector space during a search to locate relevant documents nearby. This often yields search results that are several times better than keyword search.
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Highlights
Humans speak over 7100 languages, yet the majority of language models only support the English language. This makes it incredibly challenging to build products and projects using multilingual language understanding. Cohere’s mission is to solve that by empowering our developers with technology that possesses the power of language. That’s why we’re introducing our first multilingual text understanding model that supports over 100 languages and delivers significantly better performance than existing open-source models.
Our optimized containers enable low latency inference on a diverse set of hardware accelerators available on AWS providing different cost and performance points for Sagemaker customers.
Multilingual, Semantic Search, Embeddings, Text Classification, Cross-Lingual Content Moderation
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$4.23/hr
running on ml.g5.xlarge
Model Batch Transform$14.67/hr
running on ml.g4dn.12xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$1.408/host/hr
running on ml.g5.xlarge
SageMaker Batch Transform$4.89/host/hr
running on ml.g4dn.12xlarge
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
---|---|---|
ml.p3.2xlarge | $11.475 | |
ml.g5.xlarge Vendor Recommended | $4.23 | |
ml.g5.2xlarge | $4.56 | |
ml.g4dn.xlarge | $2.2092 | |
ml.g4dn.2xlarge | $2.82 |
Usage Information
Model input and output details
Input
Summary
The model accepts JSON requests that specifies the input text to be embedded.
{ "texts": [ "hello", "goodbye" ], "truncate": "END" }
Input MIME type
application/jsonSample input data
Output
Summary
The output is a JSON object that has an array of embeddings for the input texts.
Output MIME type
application/jsonSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
AWS Infrastructure
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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