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    Sabiá-2 Small (preview)

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    Sold by: Maritaca AI 
    Deployed on AWS
    Free Trial
    A Portuguese-specialized LLM, small size

    Overview

    A Portuguese-specialized LLM, small size

    Highlights

    • A Portuguese-specialized LLM, small size

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Sabiá-2 Small (preview)

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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.
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    Usage costs (3)

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    Dimension
    Description
    Cost/host/hour
    ml.m5.4xlarge Inference (Batch)
    Recommended
    Model inference on the ml.m5.4xlarge instance type, batch mode
    $0.70
    ml.g5.8xlarge Inference (Real-Time)
    Recommended
    Model inference on the ml.g5.8xlarge instance type, real-time mode
    $0.70
    ml.g5.12xlarge Inference (Real-Time)
    Model inference on the ml.g5.12xlarge instance type, real-time mode
    $0.70

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    Usage information

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    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

    A Portuguese-specialized LLM, small size

    Additional details

    Inputs

    Summary

    { "messages": [ { "role": "string", "content": "string" } ], "chat_mode": true, "max_tokens": 1, "model": "maritalk", "do_sample": true, "temperature": 0.7, "top_p": 0.95, "repetition_penalty": 1, "stopping_tokens": [ "string" ], "stream": false, "num_tokens_per_message": 4 }

    Input MIME type
    application/json
    sugira três nomes para a minha cachorra
    https://github.com/maritaca-ai/maritalk-api/tree/main/examples/api

    Input data descriptions

    The following table describes supported input data fields for real-time inference and batch transform.

    Field name
    Description
    Constraints
    Required
    text
    Text as prompt
    Default value: "" Type: FreeText
    No

    Support

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