Llama

The LLaMA (Large Language Model Meta AI) paper describes a family of large language models developed by Meta AI to provide open and efficient foundation models for various natural language processing tasks. The LLaMA models use techniques like RMSNorm, SwiGLU activation functions, and rotary positional embeddings to improve performance and stability. The models were trained on a large-scale multilingual text corpus, focusing on efficient implementation to reduce memory usage and improve training speed. LLaMA models demonstrate strong performance in zero-shot and few-shot learning tasks across multiple benchmarks.