This section outlines a Python run-time environment set on a Windows 11 machine using Python 3.12.4 and the llama-cpp-python package, emphasizing its efficiency in handling quantized models. The hardware specifications indicate reliance on a consumer laptop, limiting inferences to CPU-only. The study focused on selecting code LLMs based on licensing, performance benchmarks, and computational demands. Five top-ranked models from the Multilingual Code Models Evaluation leaderboard were chosen to emphasize diversity without considering fine-tuned variants, ensuring a comprehensive analysis of original code generation capabilities.
In this research, a highly efficient run-time environment was established, utilizing the llama-cpp-python package to load and work with quantized LLMs for optimal performance.
The choice of LLMs was dictated by licensing, performance comparisons, and hardware constraints, focusing on original models recognized for their outstanding code generation capabilities.
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