Uses a secondary Reward Model to score LLM outputs, optimizing the LLM via Proximal Policy Optimization (PPO).

Uses a single KV head for all Query heads. It drastically reduces memory bandwidth but slightly degrades model accuracy.

With all these resources at your disposal, a structured path is essential for effective learning.

Explicitly define tokens for padding ( ), end-of-text ( ), and unknown characters ( ). 3. Infrastructure & Distributed Training