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.
Llama-3.2-NV-RerankQA-1B-v2
By:
Latest Version:
v1.3.1
Fine-tuned reranking model for multilingual, cross-lingual text question-answering retrieval, with long context support.
Product Overview
The NVIDIA NeMo Retriever Llama3.2 reranking model is optimized for providing a logit score that represents how relevant a document(s) is to a given query. The model was fine-tuned for multilingual, cross-lingual text question-answering retrieval, with support for long documents (up to 8192 tokens). 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. The reranking model is a component in a text retrieval system to improve the overall accuracy. A text retrieval system often uses an embedding model (dense) or lexical search (sparse) index to return relevant text passages given the input. A reranking model can be used to rerank the potential candidate into a final order. This model is ready for commercial use.
Key Data
Version
By
Categories
Type
Model Package
Highlights
Reorders citations by how well they match a query. This is a key step in the retrieval process, especially when the retrieval pipeline involves citations from different datastores that each have their own algorithms for measuring similarity.
Production-ready information retrieval pipeline with enterprise support
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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.
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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 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$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 to be reranked. The user can just send a list of texts to be reranked.
Input MIME type
application/jsonSample input data
Output
Summary
The output is a JSON object of reranked results
{ "rankings": [ { "index": 0, "logit": -1.2421875 }, { "index": 3, "logit": -3.029296875 }, { "index": 2, "logit": -5.41015625 }, { "index": 1, "logit": -8.2421875 } ] }
Output MIME type
application/jsonSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
Llama-3.2-NV-RerankQA-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
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