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Long-context models specifically designed for processing entire codebases in a single pass, enabling reasoning over large files and repositories.
Distinct from Long-Context Models: Distinct from general Long-Context Models: focuses on models optimized for code-specific long-context tasks rather than general text or multimodal contexts.
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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
An LLM specifically optimized for long-context reasoning over entire software repositories.
Processes input sequences up to 128,000 tokens, enabling reasoning over entire codebases in a single pass.