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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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voyage-2 Embedding Model Free trial

Latest Version:
v1
General-purpose text embedding model optimized for a balance between cost, latency, and retrieval quality. 4K context length.

    Product Overview

    Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-2 is a cutting-edge embedding model trained for general semantic retrieval tasks. The model has consistent enhancements, averaging 4.65%, across general-purpose corpora over alternatives, including OpenAI ada 002 and Cohere English v3. voyage-2 is optimized for a balance between cost, latency, and retrieval quality. Latency is 75 ms for a single query with at most 200 tokens, and throughput is 36M tokens per hour at $0.08 per 1M tokens on an ml.g6.xlarge.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • Consistent enhancements, averaging 4.65%, across general-purpose corpora over alternatives, including OpenAI ada 002 and Cohere English v3.

    • 4K token context length. Latency is 75 ms for a single query with at most 200 tokens. 36M tokens per hour at $0.08 per 1M tokens on an ml.g6.xlarge.

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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$2.112/hr

    running on ml.g5.xlarge

    Model Batch Transform$0.00/hr

    running on ml.m5.large

    Infrastructure 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$0.115/host/hr

    running on ml.m5.large

    About Free trial

    Try this product for 7 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.

    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.g5.xlarge
    Vendor Recommended
    $2.112
    ml.g5.8xlarge
    $2.2725
    ml.g5.2xlarge
    $3.045
    ml.g5.4xlarge
    $4.59
    ml.g5.16xlarge
    $7.68

    Usage Information

    Model input and output details

    Input

    Summary
    1. input: str or List[str] - Single text or list of texts.
    2. input_type: str, optional (default=None) - May also be "query" or "document".
    3. truncation: bool, optional (default=True) - True: Truncates. False: raises error if any given text exceeds the context length.
    4. encoding_format: str, optional (default=None) - Embedding format. None: float list; "base64": compressed encoding.
    Limitations for input type
    The maximum number of tokens for each text is 4K, the maximum length of the list is 128, and the total number of tokens in the list is at most 32K.
    Input MIME type
    text/csv, application/json, application/jsonlines
    Sample input data

    Output

    Summary

    The API will respond with a JSON object containing a list of embedding objects, along with other information such as model name and token usage.

    Output MIME type
    application/json, text/csv, application/jsonlines
    Sample output data

    End User License Agreement

    By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)

    Support Information

    voyage-2 Embedding Model

    Please email us at contact@voyageai.com for inquiries and customer support. Join our Discord channel: https://discord.gg/zAU7GQEmvT

    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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    Refund Policy

    Refunds to be processed under the conditions specified in EULA. Please contact contact@voyageai.com for further assistance.

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