Fine-Tuning Llama-2: Tailoring Models to Unique Applications

Fine-Tuning Llama-2: A Comprehensive Case Study for Tailoring Models to Unique Applications In this blog, we provide a thorough analysis and a practical guide for fine-tuning. We examine the Llama-2 models under three real-world use cases, and show that fine-tuning yields significant accuracy improvements across the board (in some niche cases, better than GPT-4). Experiments were carried out with

[misshiki]

“Llama-2 の微調整”