Sold by: IBM Data and AIÂ
Deployed on AWS
IBM's Granite 3.0 2B Instruct is a 2B-parameter AI model for enterprise use, excelling in multilingual and code tasks; Apache 2.0 licensed.
Overview
IBM's Granite 3.0 2B Instruct is a 2-billion-parameters LLM with a context window of 4K tokens designed for enterprise applications. It excels in tasks such as retrieval-augmented generation, classification, summarization, entity extraction, and tool utilization. Its compact size ensures efficient performance, making it suitable for integration into diverse business workflows.
Trained on over 12 trillion tokens across 12 natural languages and 116 programming languages, Granite 3.0 2B Instruct offers robust multilingual and code understanding capabilities. This third-generation model matches or outperforms similarly sized models on industry benchmarks, emphasizing performance, transparency, and safety.
Adhering to IBM's AI Ethics principles and open-source commitment, Granite 3.0 2B Instruct is released under the permissive Apache 2.0 license, making it unique in the combination of performance, flexibility and autonomy it provides to enterprise clients and the community at large.
Highlights
- IBM's Granite 3.0 2B Instruct model is a compact, versatile AI language model designed for enterprise applications. It excels in tasks such as Retrieval Augmented Generation (RAG), classification, summarization, entity extraction, and tool utilization. This compact, versatile model is designed to be fine-tuned with enterprise data and seamlessly integrated across diverse business environments or workflows.
- Released under the permissive Apache 2.0 license, the Granite 3.0 2B Instruct model offers enterprises flexibility and autonomy in deployment. IBM provides intellectual property indemnity for all Granite models on watsonx.ai, enhancing confidence for businesses integrating their data with the model.
- The Granite 3.0 2B Instruct model demonstrates strong performance across various benchmarks. Trained on over 12 trillion tokens from 12 natural languages and 116 programming languages, it utilizes a novel two-stage training method to optimize data quality and training parameters. This approach ensures robust performance in enterprise AI tasks.
Details
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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.p4d.24xlarge Inference (Real-Time) Recommended | Model inference on the ml.p4d.24xlarge instance type, real-time mode | $0.00 |
ml.g5.24xlarge Inference (Batch) Recommended | Model inference on the ml.g5.24xlarge instance type, batch mode | $0.00 |
ml.p5.48xlarge Inference (Real-Time) | Model inference on the ml.p5.48xlarge instance type, real-time mode | $0.00 |
ml.g5.12xlarge Inference (Batch) | Model inference on the ml.g5.12xlarge instance type, batch mode | $0.00 |
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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
Granite 3.0 2B Instruct is a 2-billion-parameters large language model with a context window of 4K tokens designed for enterprise applications and released under the permissive Apache 2.0 license. This model excels in tasks such as Retrieval Augmented Generation (RAG), classification, summarization, entity extraction, and tool utilization. Trained on over 12 trillion tokens from 12 natural languages and 116 programming languages, it demonstrates strong performance across various benchmarks.
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-3-2b-instruct/real_time_sample_input_data.json
https://github.com/ibm-granite-community/SageMaker/blob/main/granite-3-2b-instruct/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. The prompt template is:
```
System:
[Your instructions]
Question:
[Your question]
Answer:
```
| Type: FreeText | Yes |
Resources
Vendor resources
Support
AWS infrastructure support
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IBM Granite 3.2 Instruct is an open-source model with controllable reasoning, offering strong performance and enhanced complex thinking.
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