Sold by: IBM Data and AIÂ
Deployed on AWS
IBM Granite Embedding 30M is a fast, 30M-parameter English model delivering high-quality 384-dim embeddings for retrieval and similarity tasks.
Overview
The IBM Granite Embedding 30M English model is an innovative sentence-transformer model purpose-built for retrieval-based applications. Featuring a bi-encoder architecture, this model generates high-quality embeddings for textual inputs such as queries, passages, and documents, enabling seamless comparison through cosine similarity. The model is optimized to ensure strong alignment between query and passage embeddings. Built on a foundation of carefully curated, permissibly licensed public datasets, this model sets a high standard for performance, achieving state-of-the-art results in its respective weight class. Developed to meet enterprise-grade expectations, it is crafted transparently in accordance with IBM's AI Ethics principles and offered under the Apache 2.0 license for both research and commercial innovation.
Highlights
- With 30 million parameters and 384-dimensional embeddings, this model offers a balance between performance and speed, making it suitable for real-time applications.
- Designed for text similarity, retrieval, and search tasks, it supports seamless integration with libraries like SentenceTransformers and Hugging Face Transformers.
- Trained on permissively licensed datasets and released under the Apache 2.0 license, it is ideal for both research and commercial use.
Details
Sold by
Delivery method
Latest version
Deployed on AWS
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Pricing
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.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g5.12xlarge Inference (Batch) Recommended | Model inference on the ml.g5.12xlarge instance type, batch mode | $0.00 |
ml.m5.2xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.2xlarge instance type, real-time mode | $0.00 |
ml.g5.24xlarge Inference (Batch) | Model inference on the ml.g5.24xlarge instance type, batch mode | $0.00 |
ml.m5.xlarge Inference (Real-Time) | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.00 |
ml.m5.4xlarge Inference (Real-Time) | Model inference on the ml.m5.4xlarge instance type, real-time mode | $0.00 |
ml.m5.12xlarge Inference (Real-Time) | Model inference on the ml.m5.12xlarge instance type, real-time mode | $0.00 |
ml.g5.4xlarge Inference (Real-Time) | Model inference on the ml.g5.4xlarge instance type, real-time mode | $0.00 |
ml.g5.8xlarge Inference (Real-Time) | Model inference on the ml.g5.8xlarge instance type, real-time mode | $0.00 |
ml.g5.16xlarge Inference (Real-Time) | Model inference on the ml.g5.16xlarge instance type, real-time mode | $0.00 |
ml.g5.12xlarge Inference (Real-Time) | Model inference on the ml.g5.12xlarge instance type, real-time mode | $0.00 |
Vendor refund policy
This model is provided by IBM completely free of charge. No payment is required to use it. Therefore, there are no purchases to refund.
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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:
Version release notes
The IBM Granite Embedding 30M English model is now available under the Apache 2.0 license. This lightweight sentence-transformer model is optimized for retrieval and similarity tasks, delivering 384-dimensional embeddings with strong alignment between queries and passages. It supports use with SentenceTransformers and Transformers libraries, enabling easy integration into enterprise and research workflows.
Additional details
Inputs
- Summary
The model can be invoked by passing a prompt. Please see the sample notebook for details.
- Input MIME type
- application/json
https://github.com/ibm-granite-community/SageMaker/blob/main/granite-embedding-30m-english/real_time_sample_input_data.json
https://github.com/ibm-granite-community/SageMaker/blob/main/granite-embedding-30m-english/batch_sample_input_data.json
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
inputs | The prompt to be passed to the model. | - | Yes |
Resources
Vendor resources
Support
Vendor support
Support is not provided for this product.
AWS infrastructure support
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.
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