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.
ForecastGPT - multivariate
Latest Version:
1.2.1
This is a large language model finetuned for zero shot forecasting of time series data
Product Overview
ForecastGPT is a sophisticated AI-driven forecasting solution that leverages advanced Large Language Models (LLMs) fine-tuned on domain-specific multivariate time series datasets. It delivers unparalleled forecasting accuracy and actionable business insights, helping organizations optimize operations, plan finances, understand market dynamics, and manage human resources effectively. ForecastGPT stands out due to its real-time adaptability and learning capabilities. Fine-tuning enhances its accuracy and reliability, offering actionable insights that help businesses stay ahead in a constantly changing landscape. With ForecastGPT, businesses can anticipate trends with unparalleled accuracy and make confident, data-driven decisions.
Key Data
Version
Type
Model Package
Highlights
This model excels in zero shot forecasting of time series data by employing cutting-edge techniques that enable accurate predictions without the necessity of extensive historical data. It is adept at handling various data patterns, ensures rapid and reliable forecasts, and is fine-tuned to provide high performance even in complex scenarios.
Applications of this model span across numerous fields including finance, healthcare, and supply chain management. It enables accurate demand forecasting, aids in predicting medical events, and optimizes inventory management. Its versatility and precision make it an invaluable tool for decision-making in diverse industries.
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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$5.00/hr
running on ml.m5.4xlarge
Model Batch Transform$5,000.00/hr
running on ml.m5.4xlarge
Infrastructure PricingWith 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
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$0.922/host/hr
running on ml.m5.4xlarge
SageMaker Batch Transform$0.922/host/hr
running on ml.m5.4xlarge
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.m4.4xlarge | $5.00 | |
ml.m5.4xlarge Vendor Recommended | $5.00 | |
ml.m5d.4xlarge | $5.00 | |
ml.m5.2xlarge | $5.00 | |
ml.r5.4xlarge | $5.00 | |
ml.c5.9xlarge | $5.00 | |
ml.c5.4xlarge | $5.00 | |
ml.r5.12xlarge | $5.00 | |
ml.m4.2xlarge | $5.00 | |
ml.m5d.2xlarge | $5.00 | |
ml.c5.2xlarge | $5.00 | |
ml.m5.large | $5.00 | |
ml.r5.2xlarge | $5.00 |
Usage Information
Model input and output details
Input
Summary
The input is a json with first key as the time stamp and other keys as the independent variables.
- The Input Sequence Length and Prediction Length are fixed for this model. For a sequence of 96 points, the output is 16 points for future timestamps. But it can work with less than 97 points.
- The model can handle a variable number of features, which in turn does not affect the performance or time complexity of forecasting so it can handle both univariate and multivariate data.
Sample input data
Output
Summary
Output is a JSON of the forecasted values of all the variables (dependent and independent) for the next 16 periods
Sample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
ForecastGPT - multivariate
Business hours email support marketplaceSupp@harman.com
AWS Infrastructure
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Learn MoreRefund Policy
We do not provide any usage-related refunds at this time
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