How do specialized code models like Code Llama perform relative to general foundation models on BigCodeBench t

Abstract

Abstract: We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks. We provide multiple flavors to cover a wide range of applications: foundation models (Code Llama), Python specializations (Code Llama - Python), and instruction-following models (Code Llama - Instruct) with 7B, 13B, 34B and 70B parameters each. All models are trained on sequences of 16k tokens and show improvements on inputs with up

Research Question

How do specialized code models like Code Llama perform relative to general foundation models on BigCodeBench tasks measuring cross-library function composition versus isolated library invocation?

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