Open-source alternatives to CodeGen2

Code Llama is a large language model based on Llama 2 trained specifically for programming tasks and software development. It provides specialized model types optimized for general code generation, instruction following, and context-aware infilling. The project includes an instruction-tuned programming model for executing technical tasks via natural language prompts and a code infilling model that predicts missing sections based on surrounding source context. A large context code model is also provided to analyze extensive blocks of source code for improved coherence. The system covers capab

CodeQwen1.5 is a large language model designed for generating, completing, and analyzing code. It functions as an AI code generator capable of writing programming logic across hundreds of different languages. The model is distinguished by its long-context capabilities, allowing it to process up to one million tokens to reason across entire software repositories. It also operates as a function calling model, utilizing specialized formats to execute complex coding tasks and browser-based automation. The system supports intelligent code completion through fill-in-the-middle capabilities, which

Qwen2.5-Coder is a code-centric large language model designed to generate, complete, and analyze source code. It serves as a polyglot programming model capable of producing functional code across hundreds of different programming languages. The model is optimized for reasoning over extensive software repositories, utilizing a context window that supports up to one million tokens. It also functions as an agentic coding framework, executing multi-step workflows and browser tasks through specialized function call formats. Its capabilities include large-scale codebase analysis, intelligent parti

CodeGen is a trained large language model and program synthesis model designed to generate functional source code. It utilizes a neural network architecture to synthesize executable code from natural language descriptions or partial code snippets. The model enables automated program synthesis and AI-assisted coding by predicting and filling in missing sections of code within a program. It transforms natural language descriptions into functional programming logic to automate the creation of boilerplate and logic.

Home of CodeT5: Open Code LLMs for Code Understanding and Generation

Official research release for the family of XGen models (7B) by Salesforce AI Research: