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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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Medical LLM - 10B Free trial

Latest Version:
1.0
Enhance medical reasoning and performance in complex terminology and clinical analysis, optimized for RAG applications.

    Product Overview

    Building on the foundation of the 7B model, this 10B-parameter variant offers enhanced medical reasoning capabilities while maintaining reasonable computational requirements. It demonstrates superior performance in complex medical terminology processing, detailed clinical analysis, and nuanced healthcare documentation interpretation. The model excels in generating more comprehensive medical summaries and handling intricate clinical scenarios with greater context awareness. Its balanced architecture delivers improved accuracy in specialized medical tasks while keeping resource utilization manageable. Optimized for RAG applications, it effectively processes and synthesizes information from medical literature, clinical guidelines, and patient records. This model is ideal for healthcare institutions requiring deeper medical understanding and more sophisticated analysis capabilities while maintaining operational efficiency.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • Real-Time Inference

      • Instance Type ml.g4dn.12xlarge
      • Maximum Model Length: 32,000 tokens

      Tokens per Second during real-time inference:

      • Summarization: up to 16 tokens per second
      • QA: up to 34 tokens per second
    • Batch Transform

      • Instance Type ml.g4dn.12xlarge
      • Maximum Model Length: 32,000 tokens

      Tokens per Second during batch transform operations:

      • Summarization: up to 24 tokens per second
      • QA: up to 125 tokens per second
    • Accuracy

      • Surpasses Med-PaLM-1 with 75.19% average on medical benchmarks
      • Exceptional clinical analysis (88.19%), approaching GPT-4's performance
      • Outperforms larger models in Medical Genetics (82% vs Med-PaLM-1's 75%)
      • Maintains competitive accuracy with models 7x its size
      • Perfect balance of performance and computational efficiency

    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$9.98/hr

    running on ml.g4dn.12xlarge

    Model Batch Transform$9.98/hr

    running on ml.g4dn.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$4.89/host/hr

    running on ml.g4dn.12xlarge

    SageMaker Batch Transform$4.89/host/hr

    running on ml.g4dn.12xlarge

    About Free trial

    Try this product for 15 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.g4dn.12xlarge
    Vendor Recommended
    $9.98

    Usage Information

    Model input and output details

    Input

    Summary

    To use the model, provide input in one of the following formats: Single Input, Multiple Inputs or JSON Lines (JSONL). For a complete sample for each of the accepted formats, see the documentation here

    Input MIME type
    application/json, application/jsonlines
    Sample input data

    Output

    Summary

    The output is a JSON object or a set of JSON Lines objects that contain the generated text(s)

    JSON Format { "response": [ "model response for input 1", "model response for input 2", ... ] } JSON Lines (JSONL) Format {"response": "model response for input 1"} {"response": "model response for input 2"}

    The JSON Lines format consists of separate JSON objects, where each object represents a model response for the respective input.

    Output MIME type
    application/json, 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

    Medical LLM - 10B

    For any assistance, please reach out to support@johnsnowlabs.com.

    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 refunds are possible.

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