Safurai-Csharp: Harnessing Synthetic Data to improve language-specific
  Code LLM
Davide Cifarelli Leonardo Boiardi Alessandro Puppo Leon Jovanovic
This paper introduces Safurai-Csharp, an open-source model designed to
specialize in the generation, completion, and debugging of C# code.
Safurai-Csharp is built upon the novel CodeLlama 34B model and leverages the
EvolInstruct technique, creating a refined and expanded dataset for its
fine-tuning process. The results of its performance, a notable score of 56.33%
on the Manual MultiPL-E benchmark (Zero-Shot, Pass@1), signal its high capacity
to streamline developers' workflows and aid code learning. It shows promise in
setting new stakes in the landscape of open-source C# LLMs and hopes to inspire
more inclusive and wide-ranging development in the field of language-specific
LLMs.