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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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Llama-3.2-NV-EmbedQA-1B-v2

By:
Latest Version:
v1.3.1
Multilingual text question-answering retrieval, transforming textual information into dense vector representations.

    Product Overview

    The NVIDIA NeMo Retriever Llama3.2 embedding model is optimized for multilingual and cross-lingual text question-answering retrieval with support for long documents (up to 8192 tokens) and dynamic embedding size (Matryoshka Embeddings). This model was evaluated on 26 languages: English, Arabic, Bengali, Chinese, Czech, Danish, Dutch, Finnish, French, German, Hebrew, Hindi, Hungarian, Indonesian, Italian, Japanese, Korean, Norwegian, Persian, Polish, Portuguese, Russian, Spanish, Swedish, Thai, and Turkish. In addition to enabling multilingual and cross-lingual question-answering retrieval, this model reduces the data storage footprint by 35x through dynamic embedding sizing and support for longer token length, making it feasible to handle large-scale datasets efficiently. For additional information please contact NVIDIA: https://www.nvidia.com/en-us/data-center/lp/aws-marketplace-offer This model is ready for commercial use.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • The NeMo Retriever Llama3.2 embedding model is most suitable for users who want to build a multilingual question-and-answer application over a large text corpus, leveraging the latest dense retrieval technologies.

    • NVIDIA NIM, a part of the NVIDIA AI Enterprise software platform available on the AWS Marketplace, is a set of easy-to-use microservices designed for secure, reliable deployment of high performance AI model inferencing.

    Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us

    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$4.00/hr

    running on ml.g5.12xlarge

    Model Batch Transform$4.00/hr

    running on ml.g5.12xlarge

    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$7.09/host/hr

    running on ml.g5.12xlarge

    SageMaker Batch Transform$7.09/host/hr

    running on ml.g5.12xlarge

    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.g5.12xlarge
    Vendor Recommended
    $4.00
    ml.g5.24xlarge
    $4.00

    Usage Information

    Model input and output details

    Input

    Summary

    The model accepts JSON requests that specifies the input text to be embedded.

    { "input": ["Hello world"], "model": "nvidia/llama-3.2-nv-embedqa-1b-v2", "input_type": "query" }'

    Input MIME type
    application/json
    Sample input data

    Output

    Summary

    The output is a JSON object that has an array of embeddings for the input texts.

    Output MIME type
    application/json
    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

    Llama-3.2-NV-EmbedQA-1B-v2

    Free support via NVIDIA NIM Developer Forum: https://forums.developer.nvidia.com/c/ai-data-science/nvidia-nim/ Global enterprise support with NVIDIA AI Enterprise subscription: https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/

    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

    No refund

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