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About PolyCoder
An open-source C-focused code generation model based on GPT-2.
PolyCoder is an open-source AI code generation model trained specifically on C and other programming languages. Developed by researchers at Carnegie Mellon University, it is designed to demonstrate that smaller, specialized models trained on focused code corpora can perform competitively with larger, general-purpose code generation systems. PolyCoder is based on the GPT-2 architecture and was trained on a curated dataset of C code extracted from public GitHub repositories. Its primary goal is to offer an open, auditable alternative to proprietary models while highlighting the value of language-specific training. While its performance in general-purpose code generation tasks may lag behind models like Codex or Code Llama, it shows strong results in its target language (C), making it suitable for educational purposes, compiler researchers, or static analysis tools. PolyCoder does not currently have a commercial deployment platform but can be used via its GitHub repository and model checkpoint. Its strength lies in its open-source nature and simplicity, but its narrow language focus and relatively old base architecture (GPT-2) are limitations for broader applications.
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Example Prompts
Generate a C function for quicksort.Complete this C code snippet for file handling.Write a memory-safe C function to copy a string.