Granite-8B-Code-Instruct-4K
| Property | Value |
|---|---|
| Parameter Count | 8.05B |
| License | Apache 2.0 |
| Developer | IBM Research |
| Paper | Granite Code Models Paper |
| Release Date | May 6th, 2024 |
What is granite-8b-code-instruct-4k?
Granite-8B-Code-Instruct-4K is an advanced language model specifically designed for code intelligence and instruction following. Built by IBM Research, this model represents a significant advancement in AI-powered coding assistance, featuring 8.05 billion parameters and impressive performance across multiple programming languages.
Implementation Details
The model is fine-tuned from Granite-8B-Code-Base-4K using a carefully curated combination of permissively licensed instruction data. It demonstrates strong capabilities in code generation, with particularly impressive results in Java (58.5% pass@1), Python (57.9% pass@1), and JavaScript (52.4% pass@1).
- Built on transformer architecture with BF16 tensor type
- Trained on 8 diverse datasets including code commits, math problems, and instruction data
- Context window of 4K tokens for handling longer code sequences
- Implements sophisticated instruction-following capabilities
Core Capabilities
- Multi-language code generation with strong performance across 6 major programming languages
- Code explanation and documentation generation
- Bug fixing and code improvement suggestions
- Mathematical problem-solving capabilities
- API calling and SQL query generation
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its comprehensive training on permissively licensed data and exceptional performance across multiple programming languages, particularly in code synthesis tasks. Its balanced performance across synthesis, explanation, and bug-fixing tasks makes it versatile for various coding applications.
Q: What are the recommended use cases?
The model excels in building coding assistants, generating code solutions, explaining existing code, fixing bugs, and handling mathematical programming problems. It's particularly effective for Python, Java, and JavaScript development, though it supports multiple programming languages including C++, Go, and Rust.
