Granite Code 3B Instruct
Granite Code 3B Instruct is a large language model developed by Ibm Granite, featuring 3b parameters and released under the Apache License 2.0. It is part of the Granite Code family, designed for generative tasks with a focus on code generation, and is a decoder-only model.
Description of Granite Code 3B Instruct
Granite Code 3B Instruct is a 3B parameter model fine-tuned from Granite-3B-Code-Base-2K on instruction data to improve coding-related tasks such as logical reasoning and problem-solving. Developed by IBM Research, it is designed for coding assistants and supports multiple programming languages. The model is licensed under Apache 2.0, making it accessible for both research and commercial use. Its focus on code generation and instruction-following makes it a versatile tool for developers and AI-driven coding applications.
Parameters & Context Length of Granite Code 3B Instruct
Granite Code 3B Instruct is a 3b parameter model with a 2k context length, placing it in the small to mid-scale category of open-source LLMs. Its 3b parameter size ensures resource efficiency and fast inference, making it ideal for tasks requiring moderate complexity without heavy computational demands. The 2k context length, categorized as short, allows it to handle concise coding tasks but may limit its effectiveness for extended text generation. This balance makes it suitable for coding assistants and problem-solving scenarios where speed and simplicity are prioritized.
- Parameter Size: 3b
- Context Length: 2k
Possible Intended Uses of Granite Code 3B Instruct
The Granite Code 3B Instruct model presents possible applications in areas such as building coding assistants, generating code snippets, and assisting with problem-solving in programming. These possible uses could involve supporting developers in writing or debugging code, offering suggestions for specific programming tasks, or acting as a tool for learning and experimentation. However, the model’s 3b parameter size and 2k context length suggest it may be better suited for tasks requiring moderate complexity rather than highly intricate or extended workflows. While these possible scenarios highlight its versatility, further investigation is needed to determine how effectively it can address specific challenges or integrate into existing systems. The model’s design and licensing also open possible opportunities for collaborative development and customization, but careful evaluation is essential to align with particular goals.
- building coding assistants
- generating code snippets
- assisting with problem-solving in programming
Possible Applications of Granite Code 3B Instruct
Granite Code 3B Instruct is a possible tool for applications such as building coding assistants, generating code snippets, assisting with problem-solving in programming, and supporting educational platforms. These possible uses could involve streamlining development workflows, offering possible guidance for coding challenges, or enabling possible experimentation with code structures. However, the model’s 3b parameter size and 2k context length suggest it may be best suited for tasks requiring possible efficiency rather than extreme complexity. While these possible scenarios highlight its adaptability, each possible application must be thoroughly evaluated to ensure alignment with specific requirements.
- building coding assistants
- generating code snippets
- assisting with problem-solving in programming
- supporting educational platforms
Quantized Versions & Hardware Requirements of Granite Code 3B Instruct
Granite Code 3B Instruct with the q4 quantization is a possible choice for users seeking a balance between precision and performance, requiring a GPU with at least 12GB VRAM and 8GB–16GB VRAM for efficient operation. This version is suitable for mid-range hardware, making it possible to run on systems with 32GB RAM and adequate cooling. However, specific hardware compatibility should be verified.
- fp16, q2, q3, q4, q5, q6, q8
Conclusion
Granite Code 3B Instruct is a 3b parameter model developed by IBM Research, designed for coding tasks with a 2k context length, offering a balance between efficiency and performance for code generation and problem-solving. It supports multiple programming languages and is licensed under Apache 2.0, making it a flexible tool for developers and researchers.