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    Medical Spanish LLM - 24B

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    Deployed on AWS
    Free Trial
    Specialized 24B parameter model provides comprehensive medical language capabilities optimized for Spanish-speaking healthcare environments.

    Overview

    This specialized 24B parameter model provides comprehensive medical language capabilities optimized for Spanish-speaking healthcare environments.

    The model processes Spanish medical terminology, clinical documentation, and patient communications with high precision, bridging the language gap in medical AI. With a 32K context window, it handles extensive Spanish medical texts, including clinical notes, research papers, and patient records.

    The model summarizes complex Spanish clinical information, responds to medical queries in natural Spanish, and transforms detailed clinical documentation into concise summaries while maintaining critical details. It recognizes region-specific medical terminology variations across Spanish-speaking countries and adapts to local healthcare contexts. Healthcare providers can efficiently analyze Spanish patient histories and medical literature without translation, maintaining the nuance and precision of native medical language.

    Optimized for integration with Spanish-language medical databases and EHR systems, it enhances RAG applications in Spanish-language healthcare settings.


    IMPORTANT USAGE INFORMATION:

    After subscribing to this product and creating a SageMaker endpoint, billing occurs on an HOURLY BASIS for as long as the endpoint is running.

    -Charges apply even if the endpoint is idle and not actively processing requests.

    -To stop charges, you MUST DELETE the endpoint in your SageMaker console.

    -Simply stopping requests will NOT stop billing.

    This ensures you are only billed for the time you actively use the service.

    Highlights

    • Performance Metrics: - Achieves 84.54% accuracy on Spanish medical benchmarks - Outperforms general Medical VLM - 24B by +3.28% on Spanish content - Approaches Medical LLM - Medium performance (85.13%) at fraction of parameters - Exceeds Medical Reasoning 32B (83.32%) despite smaller size
    • Technical Specifications: - Maximum Model Length: 32K tokens - Optimized for Spanish medical terminology and documentation - Supports regional Spanish medical vocabulary variations - Maintains clinical accuracy in translation-free Spanish medical text processing - Processes Spanish medical literature with native-language understanding - Handles dialect variations across Latin American and European Spanish medical contexts
    • **Performance metrics for Real Time QA:** Instance Type: ml.g5.48xlarge * Text Completion: up to 540 tokens per second * Chat Completion: up to 790 tokens per second Instance Type: ml.p5.48xlarge * Text completion: up to 2500 tokens per second * Chat completion: up to 3300 tokens per second

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Pricing

    Free trial

    Try this product free for 15 days according to the free trial terms set by the vendor.

    Medical Spanish LLM - 24B

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (7)

     Info
    Dimension
    Description
    Cost/host/hour
    ml.g5.48xlarge Inference (Batch)
    Recommended
    Model inference on the ml.g5.48xlarge instance type, batch mode
    $19.96
    ml.g5.48xlarge Inference (Real-Time)
    Recommended
    Model inference on the ml.g5.48xlarge instance type, real-time mode
    $19.96
    ml.g6e.12xlarge Inference (Real-Time)
    Model inference on the ml.g6e.12xlarge instance type, real-time mode
    $19.96
    ml.g6e.24xlarge Inference (Real-Time)
    Model inference on the ml.g6e.24xlarge instance type, real-time mode
    $19.96
    ml.g6e.48xlarge Inference (Real-Time)
    Model inference on the ml.g6e.48xlarge instance type, real-time mode
    $19.96
    ml.p5.48xlarge Inference (Real-Time)
    Model inference on the ml.p5.48xlarge instance type, real-time mode
    $19.96
    ml.p4d.24xlarge Inference (Real-Time)
    Model inference on the ml.p4d.24xlarge instance type, real-time mode
    $19.96

    Vendor refund policy

    No refunds are possible.

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    Usage information

     Info

    Delivery details

    Amazon SageMaker model

    An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.

    Deploy the model on Amazon SageMaker AI using the following options:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    This specialized 24B parameter model provides comprehensive medical language capabilities optimized for Spanish-speaking healthcare environments. The model processes Spanish medical terminology, clinical documentation, and patient communications with high precision, bridging the language gap in medical AI.

    Additional details

    Inputs

    Summary

    Input Format

    1. Chat Completion

    Example Payload

    {
    "model": "/opt/ml/model",
    "messages": [
    {"role": "system", "content": "Eres un asistente médico útil."},
    {"role": "user", "content": "¿Qué debo hacer si tengo fiebre y dolores corporales?"}
    ],
    "max_tokens": 1024,
    "temperature": 0.7
    }

    For additional parameters:

    ChatCompletionRequest  OpenAI's Chat API 

    2. Text Completion

    Single Prompt Example

    {
    "model": "/opt/ml/model",
    "prompt": "¿Qué debo hacer si tengo fiebre y dolores corporales?",
    "max_tokens": 512,
    "temperature": 0.6
    }

    Multiple Prompts Example

    {
    "model": "/opt/ml/model",
    "prompt": [
    "ÂżCĂłmo puedo mantener una buena salud renal?",
    "¿Cuáles son los síntomas de la hipertensión?"
    ],
    "max_tokens": 512,
    "temperature": 0.6
    }

    Reference

    CompletionRequest  OpenAI's Completions API 

    Important Notes:

    • Streaming Responses: Add "stream": true to your request payload to enable streaming
    • Model Path Requirement: Always set "model": "/opt/ml/model" (SageMaker's fixed model location)
    Input MIME type
    application/json
    https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/JSL-Spanish-Medical-LLM-24B/inputs/real-time
    https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/JSL-Spanish-Medical-LLM-24B/inputs/batch

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