4 repository-uri
Large language models trained specifically on source code for generation, completion, and analysis.
Distinguishing note: None of the candidates describe the identity of a model trained specifically for code across hundreds of languages.
Explore 4 awesome GitHub repositories matching artificial intelligence & ml · Code-Specific Language Models. Refine with filters or upvote what's useful.
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
Operates as a large language model trained specifically for generating, completing, and analyzing code across hundreds of languages.
CodeLlama is a family of large language models derived from the Llama 2 architecture and specialized for producing, completing, and refactoring source code across multiple programming languages. It functions as a code generation model capable of synthesizing source code from natural language descriptions. The project includes specific model variants designed for different programming tasks. This includes instruction-tuned models trained to follow complex natural language directions and code infilling models that predict and insert missing code segments into existing files by analyzing surroun
Specialized large language models trained for producing, completing, and refactoring source code across multiple languages.
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
Provides a large language model based on Llama 2 trained specifically for programming and software development.
CodeGen este un model de limbaj mare antrenat și un model de sinteză de program conceput pentru a genera cod sursă funcțional. Utilizează o arhitectură de rețea neuronală pentru a sintetiza cod executabil din descrieri în limbaj natural sau fragmente de cod parțiale. Modelul permite sinteza automată de programe și codarea asistată de AI prin prezicerea și completarea secțiunilor lipsă de cod dintr-un program. Acesta transformă descrierile în limbaj natural în logică de programare funcțională pentru a automatiza crearea de boilerplate și logică.
Acts as a large language model specifically trained on programming languages for code synthesis and completion.