Sold by: IBM Data and AIÂ
Deployed on AWS
IBM Granite 34B Code Instruct 8K is a model fine-tuned to enhance instruction following, logical reasoning, and problem-solving skills.
Overview
The IBM Granite 34B Code Instruct 8K is a 34B parameter model with a context window of 8K tokens. Trained on permissively licensed data, it is fine-tuned to enhance instruction following, logical reasoning, and problem-solving skills.
The Granite series includes base foundational models designed for code-related tasks such as code repair, explanation, and synthesis, as well as instruct models fine-tuned on Git commits paired with human instructions and open-source, synthetically generated code instruction datasets. These models adhere to IBM's AI Ethics principles, ensuring ethical data handling, and are released under the Apache 2.0 license, making them trustworthy, enterprise-grade solutions.
Granite models are available in sizes of 3B, 8B, 20B, and 34B. They have been trained on 116 programming languages and achieve state-of-the-art results in tasks like code generation, explanation, fixing, editing, and translation.
Highlights
- The IBM Granite 34B Code Instruct 8K is a 34B-parameter model with a context window of 8K tokens, fine-tuned to enhance instruction following capabilities including logical reasoning and problem-solving skills. It achieves state-of-the-art results in tasks such as code generation, explanation, fixing, editing, and translation.
- The IBM Granite code models, with sizes ranging from 3B to 34B parameters, are developed under IBM's AI Ethics principles, using high-quality data to ensure ethical AI use, and are licensed under Apache 2.0 for both research and commercial purposes.
- The IBM Granite instruct models have been fine-tuned on Git commits across 116 programming languages, paired with human instructions and open-source, synthetically generated code instruction datasets.
Details
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Latest version
Deployed on AWS
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Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g5.48xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.48xlarge instance type, real-time mode | $0.00 |
ml.g5.48xlarge Inference (Batch) Recommended | Model inference on the ml.g5.48xlarge instance type, batch mode | $0.00 |
ml.g5.12xlarge Inference (Real-Time) | Model inference on the ml.g5.12xlarge instance type, real-time mode | $0.00 |
ml.g5.24xlarge Inference (Real-Time) | Model inference on the ml.g5.24xlarge 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 |
ml.g5.24xlarge Inference (Batch) | Model inference on the ml.g5.24xlarge 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-34B-Code-Instruct-8K is a 34B-parameter model with a context window size of 8K tokens, fine-tuned from Granite-34B-Code-Base-8K on a combination of permissively licensed instruction data, aimed at enhancing instruction-following capabilities, including logical reasoning and problem-solving skills.
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-34b-code-instruct-8k/real_time_sample_input_data.json
https://github.com/ibm-granite-community/SageMaker/blob/main/granite-34b-code-instruct-8k/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
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