LLaMA 3

LLaMA 3 is a family of large language models (LLMs) focusing on improving efficiency and performance across various tasks, including code generation, mathematical reasoning, and multilingual capabilities. Current research emphasizes techniques like parameter-efficient fine-tuning and selective layer enhancement to optimize knowledge injection and reduce computational costs, particularly for quantization and context length extension. These advancements are significant for expanding access to powerful LLMs and facilitating research in diverse scientific fields, as well as improving the efficiency and capabilities of practical applications.