Audience
Developers interested in a powerful AI coding model
About Granite Code
We introduce the Granite series of decoder-only code models for code generative tasks (e.g., fixing bugs, explaining code, documenting code), trained with code written in 116 programming languages. A comprehensive evaluation of the Granite Code model family on diverse tasks demonstrates that our models consistently reach state-of-the-art performance among available open source code LLMs.
The key advantages of Granite Code models include:
All-rounder Code LLM: Granite Code models achieve competitive or state-of-the-art performance on different kinds of code-related tasks, including code generation, explanation, fixing, editing, translation, and more. Demonstrating their ability to solve diverse coding tasks.
Trustworthy Enterprise-Grade LLM: All our models are trained on license-permissible data collected following IBM's AI Ethics principles and guided by IBM’s Corporate Legal team for trustworthy enterprise usage.
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IBM Granite
IBM® Granite™ is a family of artificial intelligence (AI) models purpose-built for business, engineered from scratch to help ensure trust and scalability in AI-driven applications. Open source Granite models are available today.
We make AI as accessible as possible for as many developers as possible. That’s why we have open-sourced core Granite Code, Time Series, Language, and GeoSpatial models and made them available on Hugging Face under permissive Apache 2.0 license that enables broad, unencumbered commercial usage.
All Granite models are trained on carefully curated data, with industry-leading levels of transparency about the data that went into them. We have also open-sourced the tools we use to ensure the data is high quality and up to the standards that enterprise-grade applications demand.
Learn more
Code Llama
Code Llama is a large language model (LLM) that can use text prompts to generate code. Code Llama is state-of-the-art for publicly available LLMs on code tasks, and has the potential to make workflows faster and more efficient for current developers and lower the barrier to entry for people who are learning to code. Code Llama has the potential to be used as a productivity and educational tool to help programmers write more robust, well-documented software.
Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts.
Code Llama is free for research and commercial use.
Code Llama is built on top of Llama 2 and is available in three models:
Code Llama, the foundational code model;
Codel Llama - Python specialized for Python;
and Code Llama - Instruct, which is fine-tuned for understanding natural language instructions.
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Codestral
We introduce Codestral, our first-ever code model. Codestral is an open-weight generative AI model explicitly designed for code generation tasks. It helps developers write and interact with code through a shared instruction and completion API endpoint. As it masters code and English, it can be used to design advanced AI applications for software developers.
Codestral is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash. It also performs well on more specific ones like Swift and Fortran. This broad language base ensures Codestral can assist developers in various coding environments and projects.
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CodeQwen
CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.
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Pricing
Starting Price:
Free
Pricing Details:
Open source
Free Version:
Free Version available.
Integrations
Company Information
IBM
Founded: 1911
United States
www.ibm.com/granite
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Cloud
Training
Documentation