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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Jina Embeddings v3
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Latest Version:
1.3
New State-of-the-Art Multilingual Embeddings With Task LoRA
Product Overview
jina-embeddings-v3 is a multilingual multi-task text embedding model designed for a variety of NLP applications. Based on the Jina-XLM-RoBERTa architecture, this model supports Rotary Position Embeddings to handle long input sequences up to 8192 tokens. Additionally, it features 5 LoRA adapters to generate task-specific embeddings efficiently.
Key Data
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Model Package
Highlights
Extended Sequence Length: Supports up to 8192 tokens with RoPE .
Task-Specific Embedding: Customize embeddings through the task argument with the following options:
- retrieval.query: Used for query embeddings in asymmetric retrieval tasks
- retrieval.passage: Used for passage embeddings in asymmetric retrieval tasks
- separation: Used for embeddings in clustering and re-ranking applications
- classification: Used for embeddings in classification tasks
- text-matching: Used for embeddings in tasks that quantify similarity between two texts, such as STS or symmetric retrieval tasks
Matryoshka Embeddings : Supports flexible embedding sizes (32, 64, 128, 256, 512, 768, 1024), allowing for truncating embeddings to fit your application.
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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$2.50/hr
running on ml.g5.xlarge
Model Batch Transform$2.50/hr
running on ml.g5.xlarge
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$1.408/host/hr
running on ml.g5.xlarge
SageMaker Batch Transform$1.408/host/hr
running on ml.g5.xlarge
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.p2.xlarge | $2.30 | |
ml.g4dn.4xlarge | $4.00 | |
ml.g4dn.16xlarge | $14.50 | |
ml.p2.16xlarge | $35.00 | |
ml.p3.16xlarge | $48.25 | |
ml.g5.xlarge Vendor Recommended | $2.50 | |
ml.g5.8xlarge | $18.25 | |
ml.g5.12xlarge | $27.50 | |
ml.g4dn.2xlarge | $2.20 | |
ml.g5.4xlarge | $9.30 | |
ml.g5.16xlarge | $35.00 | |
ml.p3.8xlarge | $25.00 | |
ml.p3.2xlarge | $7.00 | |
ml.p2.8xlarge | $18.00 | |
ml.g4dn.8xlarge | $7.60 | |
ml.g4dn.12xlarge | $11.25 | |
ml.g5.2xlarge | $4.75 | |
ml.g4dn.xlarge | $1.50 | |
ml.g5.48xlarge | $90.00 | |
ml.g5.24xlarge | $52.00 |
Usage Information
Model input and output details
Input
Summary
The model accepts JSON inputs. Texts must be passed in the following format.
{ "data": [ { "text": "How is the weather today?" }, { "text": "What's the color of an orange?" } ], "parameters": { "task": "text-matching", "late_chunking": false, "dimensions": 1024 } }
Input MIME type
text/csvSample input data
Output
Summary
A JSON object with an array of IDs, embeddings and usages.
Output MIME type
text/csvSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
Jina Embeddings v3
We provide support for this model package through our enterprise support channel.
AWS Infrastructure
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Learn MoreRefund Policy
Refunds to be processed under the conditions specified in EULA.
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