Modern decoder-only LLM'lerde (LLaMA, Mistral, Qwen) mimari trendler nelerdir?

Modern decoder-only Large Language Models (LLMs) like LLaMA, Mistral, Qwen follow several architectural trends:

• Parameter increase while maintaining efficiency: models grow in size but are optimized for more efficient training and inference.

• Use of efficient attention mechanisms: implementing optimizations in self-attention to reduce computational complexity.

• Modularity and hybrid architectures: sometimes combining different layer types or using specialized blocks to improve performance.

• Focus on training with less data and better generalization: through improved pre-training methods and regularization.

• Optimization for specific tasks and hardware platforms: models adapt to the requirements of real-world applications and available resources.

These trends aim to improve text generation quality, reduce training costs, and enhance scalability.