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.
voyage-2 Embedding Model Free trial
By:
Latest Version:
v1
General-purpose text embedding model optimized for a balance between cost, latency, and retrieval quality. 4K context length.
Product Overview
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-2 is a cutting-edge embedding model trained for general semantic retrieval tasks. The model has consistent enhancements, averaging 4.65%, across general-purpose corpora over alternatives, including OpenAI ada 002 and Cohere English v3. voyage-2 is optimized for a balance between cost, latency, and retrieval quality. Latency is 75 ms for a single query with at most 200 tokens, and throughput is 36M tokens per hour at $0.08 per 1M tokens on an ml.g6.xlarge.
Key Data
Version
Type
Model Package
Highlights
Consistent enhancements, averaging 4.65%, across general-purpose corpora over alternatives, including OpenAI ada 002 and Cohere English v3.
4K token context length. Latency is 75 ms for a single query with at most 200 tokens. 36M tokens per hour at $0.08 per 1M tokens on an ml.g6.xlarge.
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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$2.112/hr
running on ml.g5.xlarge
Model Batch Transform$0.00/hr
running on ml.m5.large
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$0.115/host/hr
running on ml.m5.large
About Free trial
Try this product for 7 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.
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.xlarge Vendor Recommended | $2.112 | |
ml.g5.8xlarge | $2.2725 | |
ml.g5.2xlarge | $3.045 | |
ml.g5.4xlarge | $4.59 | |
ml.g5.16xlarge | $7.68 |
Usage Information
Model input and output details
Input
Summary
input
:str
orList[str]
- Single text or list of texts.input_type
:str
, optional (default=None
) - May also be"query"
or"document"
.truncation
:bool
, optional (default=True
) -True
: Truncates.False
: raises error if any given text exceeds the context length.encoding_format
:str
, optional (default=None
) - Embedding format.None
: float list;"base64"
: compressed encoding.
Limitations for input type
The maximum number of tokens for each text is 4K, the maximum length of the list is 128, and the total number of tokens in the list is at most 32K.
Input MIME type
text/csv, application/json, application/jsonlinesSample input data
Output
Summary
The API will respond with a JSON object containing a list of embedding objects, along with other information such as model name and token usage.
Output MIME type
application/json, text/csv, application/jsonlinesSample output data
Sample notebook
Additional Resources
End User License Agreement
By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)
Support Information
voyage-2 Embedding Model
Please email us at contact@voyageai.com for inquiries and customer support. Join our Discord channel: https://discord.gg/zAU7GQEmvT
AWS Infrastructure
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Learn MoreRefund Policy
Refunds to be processed under the conditions specified in EULA. Please contact contact@voyageai.com for further assistance.
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